diff --git a/.github/workflows/check.yaml b/.github/workflows/check.yaml index bfb1713e..7e6b468b 100644 --- a/.github/workflows/check.yaml +++ b/.github/workflows/check.yaml @@ -56,12 +56,17 @@ jobs: - {os: windows-latest, r: 'devel', allowfail: false} - {os: windows-latest, r: 'release', allowfail: false} - {os: windows-latest, r: 'oldrel', allowfail: false} - - {os: ubuntu-20.04, r: 'devel', allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"} - - {os: ubuntu-20.04, r: 'release', allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"} - - {os: ubuntu-20.04, r: 'oldrel', allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"} + - {os: ubuntu-20.04, r: 'devel', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"} + - {os: ubuntu-20.04, r: 'release', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"} + - {os: ubuntu-20.04, r: 'oldrel', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"} + - {os: ubuntu-20.04, r: '4.0', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"} + - {os: ubuntu-20.04, r: '3.6', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"} + - {os: ubuntu-20.04, r: '3.5', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"} + - {os: ubuntu-20.04, r: '3.4', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"} + - {os: ubuntu-20.04, r: '3.3', allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"} - {os: ubuntu-20.04, r: '3.2', allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"} - {os: ubuntu-20.04, r: '3.1', allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"} - - {os: ubuntu-20.04, r: '3.0', allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"} + - {os: ubuntu-20.04, r: '3.0', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"} - {os: ubuntu-16.04, r: 'devel', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"} - {os: ubuntu-16.04, r: 'release', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"} - {os: ubuntu-16.04, r: 'oldrel', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"} @@ -69,7 +74,7 @@ jobs: - {os: ubuntu-16.04, r: '3.6', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"} - {os: ubuntu-16.04, r: '3.5', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"} - {os: ubuntu-16.04, r: '3.4', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"} - - {os: ubuntu-16.04, r: '3.3', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"} + - {os: ubuntu-16.04, r: '3.3', allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"} - {os: ubuntu-16.04, r: '3.2', allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"} - {os: ubuntu-16.04, r: '3.1', allowfail: true, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"} - {os: ubuntu-16.04, r: '3.0', allowfail: false, rspm: "https://packagemanager.rstudio.com/cran/__linux__/xenial/latest"} diff --git a/DESCRIPTION b/DESCRIPTION index 482fa342..af8113f4 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,6 +1,6 @@ Package: AMR -Version: 1.5.0 -Date: 2021-01-05 +Version: 1.5.0.9000 +Date: 2021-01-12 Title: Antimicrobial Resistance Analysis Authors@R: c( person(role = c("aut", "cre"), diff --git a/NAMESPACE b/NAMESPACE index 872de409..370d824e 100755 --- a/NAMESPACE +++ b/NAMESPACE @@ -2,19 +2,23 @@ S3method("[",ab) S3method("[",disk) +S3method("[",isolate_identifier) S3method("[",mic) S3method("[",mo) S3method("[<-",ab) S3method("[<-",disk) +S3method("[<-",isolate_identifier) S3method("[<-",mic) S3method("[<-",mo) S3method("[<-",rsi) S3method("[[",ab) S3method("[[",disk) +S3method("[[",isolate_identifier) S3method("[[",mic) S3method("[[",mo) S3method("[[<-",ab) S3method("[[<-",disk) +S3method("[[<-",isolate_identifier) S3method("[[<-",mic) S3method("[[<-",mo) S3method("[[<-",rsi) @@ -31,6 +35,7 @@ S3method(barplot,mic) S3method(barplot,rsi) S3method(c,ab) S3method(c,disk) +S3method(c,isolate_identifier) S3method(c,mic) S3method(c,mo) S3method(c,rsi) @@ -48,6 +53,7 @@ S3method(print,ab) S3method(print,bug_drug_combinations) S3method(print,catalogue_of_life_version) S3method(print,disk) +S3method(print,isolate_identifier) S3method(print,mic) S3method(print,mo) S3method(print,mo_renamed) @@ -61,6 +67,7 @@ S3method(summary,mo) S3method(summary,rsi) S3method(unique,ab) S3method(unique,disk) +S3method(unique,isolate_identifier) S3method(unique,mic) S3method(unique,mo) S3method(unique,rsi) @@ -113,6 +120,7 @@ export(count_all) export(count_df) export(count_resistant) export(count_susceptible) +export(eucast_dosage) export(eucast_exceptional_phenotypes) export(eucast_rules) export(facet_rsi) @@ -153,6 +161,7 @@ export(is.mo) export(is.rsi) export(is.rsi.eligible) export(is_new_episode) +export(isolate_identifier) export(key_antibiotics) export(key_antibiotics_equal) export(kurtosis) @@ -175,6 +184,7 @@ export(mo_info) export(mo_is_gram_negative) export(mo_is_gram_positive) export(mo_is_intrinsic_resistant) +export(mo_is_yeast) export(mo_kingdom) export(mo_matching_score) export(mo_name) diff --git a/NEWS.md b/NEWS.md index 8acfbb5b..fa2afa83 100755 --- a/NEWS.md +++ b/NEWS.md @@ -1,6 +1,39 @@ -# AMR 1.5.0 +# AMR 1.5.0.9000 +## Last updated: 12 January 2021 +*Note: the rules of 'EUCAST Clinical Breakpoints v11.0 (2021)' will also be added in this next release, to be expected in February/March 2021.* -*Note: the rules of 'EUCAST Clinical Breakpoints v11.0 (2021)' will be added in the next release, to be expected in February/March 2021.* +### New +* Support for EUCAST Clinical Breakpoints v11.0 (2021), effective in the `eucast_rules()` function and in `as.rsi()` to interpret MIC and disk diffusion values. This is now the default guideline in this package. +* Function `eucast_dosage()` to to get advised dosages of a certain bug-drug combination based on EUCAST dosage data +* Data set `dosage` to fuel the new `eucast_dosage()` function and to make this data available in a structured way +* Function `isolate_identifier()`, which will paste a microorganism code with all antimicrobial results of a data set into one string for each row. This is useful to compare isolates, e.g. between institutions or regions, when there is no genotyping available. +* Function `mo_is_yeast()`, which determines whether a microorganism is a member of the taxonomic class Saccharomycetes or the taxonomic order Saccharomycetales: + ```r + mo_kingdom(c("Aspergillus", "Candida")) + #> [1] "Fungi" "Fungi" + + mo_is_yeast(c("Aspergillus", "Candida")) + #> [1] FALSE TRUE + + # usage for filtering data: + example_isolates[which(mo_is_yeast()), ] # base R + example_isolates %>% filter(mo_is_yeast()) # dplyr + ``` + The `mo_type()` function has also been updated to reflect this change: + ```r + mo_type(c("Aspergillus", "Candida")) + # [1] "Fungi" "Yeasts" + mo_type(c("Aspergillus", "Candida"), language = "es") # also supported: de, nl, fr, it, pt + #> [1] "Hongos" "Levaduras" + ``` + +### Changed +* Using functions without setting a data set (e.g., `mo_is_gram_negative()`, `mo_is_gram_positive()`, `mo_is_intrinsic_resistant()`, `first_isolate()`, `mdro()`) now work with `dplyr`s `group_by()` again +* Updated the data set `microorganisms.codes` (which contains popular LIS and WHONET codes for microorganisms) for some species of *Mycobacterium* that previously incorrectly returned *M. africanum* +* Added Pretomanid (PMD, J04AK08) to the `antibiotics` data set + + +# AMR 1.5.0 ### New * Functions `get_episode()` and `is_new_episode()` to determine (patient) episodes which are not necessarily based on microorganisms. The `get_episode()` function returns the index number of the episode per group, while the `is_new_episode()` function returns values `TRUE`/`FALSE` to indicate whether an item in a vector is the start of a new episode. They also support `dplyr`s grouping (i.e. using `group_by()`): diff --git a/R/aa_helper_functions.R b/R/aa_helper_functions.R index dd262024..afa9e53a 100755 --- a/R/aa_helper_functions.R +++ b/R/aa_helper_functions.R @@ -81,10 +81,13 @@ check_dataset_integrity <- function() { overwritten <- data_in_pkg[data_in_pkg %in% data_in_globalenv] # exception for example_isolates overwritten <- overwritten[overwritten != "example_isolates"] - stop_if(length(overwritten) > 0, - "the following data set is overwritten by your global environment and prevents the AMR package from working correctly:\n", - paste0("'", overwritten, "'", collapse = ", "), - ".\nPlease rename your object before using this function.", call = FALSE) + if (length(overwritten) > 0) { + warning_(ifelse(length(overwritten) == 1, + "The following data set is overwritten by your global environment and prevents the AMR package from working correctly: ", + "The following data sets are overwritten by your global environment and prevent the AMR package from working correctly: "), + paste0("'", overwritten, "'", collapse = ", "), + ".\nPlease rename your object(s).", call = FALSE) + } # check if other packages did not overwrite our data sets tryCatch({ check_microorganisms <- all(c("mo", "fullname", "kingdom", "phylum", @@ -439,6 +442,20 @@ create_ab_documentation <- function(ab) { out } +vector_or <- function(v, quotes = TRUE, reverse = FALSE) { + # makes unique and sorts, and this also removed NAs + v <- sort(unique(v)) + if (length(v) == 1) { + return(paste0(ifelse(quotes, '"', ""), v, ifelse(quotes, '"', ""))) + } + if (reverse == TRUE) { + v <- rev(v) + } + # all commas except for last item, so will become '"val1", "val2", "val3" or "val4"' + paste0(paste0(ifelse(quotes, '"', ""), v[seq_len(length(v) - 1)], ifelse(quotes, '"', ""), collapse = ", "), + " or ", paste0(ifelse(quotes, '"', ""), v[length(v)], ifelse(quotes, '"', ""))) +} + # a check for every single argument in all functions meet_criteria <- function(object, allow_class = NULL, @@ -463,15 +480,6 @@ meet_criteria <- function(object, return(invisible()) } - vector_or <- function(v, quotes) { - if (length(v) == 1) { - return(paste0(ifelse(quotes, '"', ""), v, ifelse(quotes, '"', ""))) - } - # all commas except for last item, so will become '"val1", "val2", "val3" or "val4"' - paste0(paste0(ifelse(quotes, '"', ""), v[seq_len(length(v) - 1)], ifelse(quotes, '"', ""), collapse = ", "), - " or ", paste0(ifelse(quotes, '"', ""), v[length(v)], ifelse(quotes, '"', ""))) - } - if (!is.null(allow_class)) { stop_ifnot(inherits(object, allow_class), "argument `", obj_name, "` must ", # ifelse(allow_NULL, "be NULL or must ", ""), @@ -527,24 +535,38 @@ meet_criteria <- function(object, } get_current_data <- function(arg_name, call) { + # try dplyr::cur_data_all() first to support dplyr groups + # only useful for e.g. dplyr::filter(), dplyr::mutate() and dplyr::summarise() + # not useful (throws error) with e.g. dplyr::select() - but that will be caught later in this function + cur_data_all <- import_fn("cur_data_all", "dplyr", error_on_fail = FALSE) + if (!is.null(cur_data_all)) { + out <- tryCatch(cur_data_all(), error = function(e) NULL) + if (is.data.frame(out)) { + return(out) + } + } + if (as.double(R.Version()$major) + (as.double(R.Version()$minor) / 10) < 3.2) { + # R-3.0 and R-3.1 do not have an `x` element in the call stack, rendering this function useless if (is.na(arg_name)) { + # like in carbapenems() etc. warning_("this function can only be used in R >= 3.2", call = call) return(data.frame()) } else { stop_("argument `", arg_name, "` is missing with no default", call = call) } } - + # try a (base R) method, by going over the complete system call stack with sys.frames() not_set <- TRUE frms <- lapply(sys.frames(), function(el) { - if (".Generic" %in% names(el)) { - if (tryCatch(not_set == TRUE && ".data" %in% names(el) && is.data.frame(el$`.data`), error = function(e) FALSE)) { + if (not_set == TRUE && ".Generic" %in% names(el)) { + if (tryCatch(".data" %in% names(el) && is.data.frame(el$`.data`), error = function(e) FALSE)) { # dplyr? - an element `.data` will be in the system call stack + # will be used in dplyr::select() (but not in dplyr::filter(), dplyr::mutate() or dplyr::summarise()) not_set <<- FALSE el$`.data` - } else if (tryCatch(not_set == TRUE && any(c("x", "xx") %in% names(el)), error = function(e) FALSE)) { + } else if (tryCatch(any(c("x", "xx") %in% names(el)), error = function(e) FALSE)) { # otherwise try base R: # an element `x` will be in this environment for only cols, e.g. `example_isolates[, carbapenems()]` # an element `xx` will be in this environment for rows + cols, e.g. `example_isolates[c(1:3), carbapenems()]` @@ -574,9 +596,7 @@ get_current_data <- function(arg_name, call) { stop_("this function must be used inside valid dplyr selection verbs or inside a data.frame call", call = call) } else { - stop_("argument `", arg_name, "` is missing with no default ", - "or function not used inside a valid dplyr verb", - call = call) + stop_("argument `", arg_name, "` is missing with no default", call = call) } } @@ -595,19 +615,19 @@ unique_call_id <- function(entire_session = FALSE) { remember_thrown_message <- function(fn, entire_session = FALSE) { # this is to prevent that messages/notes will be printed for every dplyr group # e.g. this would show a msg 4 times: example_isolates %>% group_by(hospital_id) %>% filter(mo_is_gram_negative()) - assign(x = paste0("thrown_msg_", fn), + assign(x = paste0("thrown_msg.", fn), value = unique_call_id(entire_session = entire_session), envir = pkg_env) } message_not_thrown_before <- function(fn, entire_session = FALSE) { - is.null(pkg_env[[paste0("thrown_msg_", fn)]]) || !identical(pkg_env[[paste0("thrown_msg_", fn)]], unique_call_id(entire_session)) + is.null(pkg_env[[paste0("thrown_msg.", fn)]]) || !identical(pkg_env[[paste0("thrown_msg.", fn)]], unique_call_id(entire_session)) } reset_all_thrown_messages <- function() { # for unit tests, where the environment and highest system call do not change pkg_env_contents <- ls(envir = pkg_env) - rm(list = pkg_env_contents[pkg_env_contents %like% "^thrown_msg_"], + rm(list = pkg_env_contents[pkg_env_contents %like% "^thrown_msg."], envir = pkg_env) } diff --git a/R/ab.R b/R/ab.R index cd083967..331893c7 100755 --- a/R/ab.R +++ b/R/ab.R @@ -160,6 +160,12 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = TRUE, ...) { from_text <- character(0) } + # old code for phenoxymethylpenicillin (Peni V) + if (x[i] == "PNV") { + x_new[i] <- "PHN" + next + } + # exact name found <- antibiotics[which(AB_lookup$generalised_name == x[i]), ]$ab if (length(found) > 0) { diff --git a/R/data.R b/R/data.R index 866f2eb0..e52f47f5 100755 --- a/R/data.R +++ b/R/data.R @@ -95,7 +95,14 @@ #' - `source`\cr Either "CoL", "DSMZ" (see Source) or "manually added" #' - `prevalence`\cr Prevalence of the microorganism, see [as.mo()] #' - `snomed`\cr SNOMED code of the microorganism. Use [mo_snomed()] to retrieve it quickly, see [mo_property()]. -#' @details Manually added were: +#' @details +#' Please note that entries are only based on the Catalogue of Life and the LPSN (see below). Since these sources incorporate entries based on (recent) publications in the International Journal of Systematic and Evolutionary Microbiology (IJSEM), it can happen that the year of publication is sometimes later than one might expect. +#' +#' For example, *Staphylococcus pettenkoferi* was newly named in Diagnostic Microbiology and Infectious Disease in 2002 (PMID 12106949), but it was not before 2007 that a publication in IJSEM followed (PMID 17625191). Consequently, the AMR package returns 2007 for `mo_year("S. pettenkoferi")`. +#' +#' ### Manually additions +#' For convenience, some entries were added manually: +#' #' - 11 entries of *Streptococcus* (beta-haemolytic: groups A, B, C, D, F, G, H, K and unspecified; other: viridans, milleri) #' - 2 entries of *Staphylococcus* (coagulase-negative (CoNS) and coagulase-positive (CoPS)) #' - 3 entries of *Trichomonas* (*Trichomonas vaginalis*, and its family and genus) @@ -269,3 +276,21 @@ catalogue_of_life <- list( #' # [1] "Enterococcus casseliflavus" "Enterococcus gallinarum" #' } "intrinsic_resistant" + +#' Data set with treatment dosages as defined by EUCAST +#' +#' EUCAST breakpoints used in this package are based on the dosages in this data set. They can be retrieved with [eucast_dosage()]. +#' @format A [data.frame] with `r format(nrow(dosage), big.mark = ",")` observations and `r ncol(dosage)` variables: +#' - `ab`\cr Antibiotic ID as used in this package (such as `AMC`), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available +#' - `name`\cr Official name of the antimicrobial agent as used by WHONET/EARS-Net or the WHO +#' - `type`\cr Type of the dosage, either `r vector_or(dosage$type)` +#' - `dose`\cr Dose, such as "2 g" or "25 mg/kg" +#' - `dose_times`\cr Dose, such as "2 g" or "25 mg/kg" +#' - `administration`\cr Route of administration, either `r vector_or(dosage$administration)` +#' - `notes`\cr Additional dosage notes +#' - `original_txt`\cr Original text in the PDF file of EUCAST +#' - `eucast_version`\cr Version number of the EUCAST Clinical Breakpoints guideline to which these dosages apply +#' @details `r format_eucast_version_nr(11.0)` are based on the dosages in this data set. +#' @inheritSection AMR Reference data publicly available +#' @inheritSection AMR Read more on our website! +"dosage" diff --git a/R/eucast_rules.R b/R/eucast_rules.R index 79037442..00204a89 100755 --- a/R/eucast_rules.R +++ b/R/eucast_rules.R @@ -23,12 +23,16 @@ # how to conduct AMR analysis: https://msberends.github.io/AMR/ # # ==================================================================== # -# add new version numbers here, and add the rules themselves to "data-raw/eucast_rules.tsv" -# (running "data-raw/internals.R" will process that TSV file) -EUCAST_VERSION_BREAKPOINTS <- list("10.0" = list(version_txt = "v10.0", +# add new version numbers here, and add the rules themselves to "data-raw/eucast_rules.tsv" and rsi_translation +# (running "data-raw/internals.R" will process the TSV file) +EUCAST_VERSION_BREAKPOINTS <- list("11.0" = list(version_txt = "v11.0", + year = 2021, + title = "'EUCAST Clinical Breakpoint Tables'", + url = "https://www.eucast.org/clinical_breakpoints/"), + "10.0" = list(version_txt = "v10.0", year = 2020, - title = "'EUCAST Clinical Breakpoints'", - url = "https://www.eucast.org/clinical_breakpoints/")) + title = "'EUCAST Clinical Breakpoint Tables'", + url = "https://www.eucast.org/ast_of_bacteria/previous_versions_of_documents/")) EUCAST_VERSION_EXPERT_RULES <- list("3.1" = list(version_txt = "v3.1", year = 2016, title = "'EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes'", @@ -44,17 +48,17 @@ format_eucast_version_nr <- function(version, markdown = TRUE) { version <- format(version, nsmall = 1) if (markdown == TRUE) { paste0("[", lst[[version]]$title, " ", lst[[version]]$version_txt, "](", lst[[version]]$url, ")", - " from ", lst[[version]]$year) + " (", lst[[version]]$year, ")") } else { paste0(lst[[version]]$title, " ", lst[[version]]$version_txt, - " from ", lst[[version]]$year) + " (", lst[[version]]$year, ")") } } #' Apply EUCAST rules #' #' @description -#' Apply rules for clinical breakpoints and intrinsic resistance as defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST, ), see *Source*. +#' Apply rules for clinical breakpoints and intrinsic resistance as defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST, ), see *Source*. Use [eucast_dosage()] to get advised dosages of a certain bug-drug combination, which is based on the [dosage] data set. #' #' To improve the interpretation of the antibiogram before EUCAST rules are applied, some non-EUCAST rules can applied at default, see Details. #' @inheritSection lifecycle Stable lifecycle @@ -62,11 +66,12 @@ format_eucast_version_nr <- function(version, markdown = TRUE) { #' @param info a logical to indicate whether progress should be printed to the console, defaults to only print while in interactive sessions #' @param rules a character vector that specifies which rules should be applied. Must be one or more of `"breakpoints"`, `"expert"`, `"other"`, `"all"`, and defaults to `c("breakpoints", "expert")`. The default value can be set to another value, e.g. using `options(AMR_eucastrules = "all")`. #' @param verbose a [logical] to turn Verbose mode on and off (default is off). In Verbose mode, the function does not apply rules to the data, but instead returns a data set in logbook form with extensive info about which rows and columns would be effected and in which way. Using Verbose mode takes a lot more time. -#' @param version_breakpoints the version number to use for the EUCAST Clinical Breakpoints guideline. Currently supported: `r paste0(names(EUCAST_VERSION_BREAKPOINTS), collapse = ", ")`. -#' @param version_expertrules the version number to use for the EUCAST Expert Rules and Intrinsic Resistance guideline. Currently supported: `r paste0(names(EUCAST_VERSION_EXPERT_RULES), collapse = ", ")`. +#' @param version_breakpoints the version number to use for the EUCAST Clinical Breakpoints guideline. Can be either `r vector_or(names(EUCAST_VERSION_BREAKPOINTS), reverse = TRUE)`. +#' @param version_expertrules the version number to use for the EUCAST Expert Rules and Intrinsic Resistance guideline. Can be either `r vector_or(names(EUCAST_VERSION_EXPERT_RULES), reverse = TRUE)`. #' @param ampc_cephalosporin_resistance a character value that should be applied for AmpC de-repressed cephalosporin-resistant mutants, defaults to `NA`. Currently only works when `version_expertrules` is `3.2`; '*EUCAST Expert Rules v3.2 on Enterobacterales*' states that susceptible (S) results of cefotaxime, ceftriaxone and ceftazidime should be reported with a note, or results should be suppressed (emptied) for these agents. A value of `NA` for this argument will remove results for these agents, while e.g. a value of `"R"` will make the results for these agents resistant. Use `NULL` to not alter the results for AmpC de-repressed cephalosporin-resistant mutants. \cr For *EUCAST Expert Rules* v3.2, this rule applies to: *`r gsub("[)(^]", "", gsub("|", ", ", eucast_rules_file[which(eucast_rules_file$reference.version == 3.2 & eucast_rules_file$reference.rule %like% "ampc"), "this_value"][1], fixed = TRUE))`*. -#' #' @param ... column name of an antibiotic, please see section *Antibiotics* below +#' @param ab any (vector of) text that can be coerced to a valid antibiotic code with [as.ab()] +#' @param administration route of administration, either `r vector_or(dosage$administration)` #' @inheritParams first_isolate #' @details #' **Note:** This function does not translate MIC values to RSI values. Use [as.rsi()] for that. \cr @@ -101,6 +106,7 @@ format_eucast_version_nr <- function(version, markdown = TRUE) { #' - EUCAST Intrinsic Resistance and Unusual Phenotypes. Version 3.2, 2020. [(link)](https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/2020/Intrinsic_Resistance_and_Unusual_Phenotypes_Tables_v3.2_20200225.pdf) #' - EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 9.0, 2019. [(link)](https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_9.0_Breakpoint_Tables.xlsx) #' - EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 10.0, 2020. [(link)](https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_10.0_Breakpoint_Tables.xlsx) +#' - EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 11.0, 2021. [(link)](https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_11.0_Breakpoint_Tables.xlsx) #' @inheritSection AMR Reference data publicly available #' @inheritSection AMR Read more on our website! #' @examples @@ -144,12 +150,14 @@ format_eucast_version_nr <- function(version, markdown = TRUE) { #' # containing all details about the transformations: #' c <- eucast_rules(a, verbose = TRUE) #' } +#' +#' eucast_dosage(c("tobra", "genta", "cipro"), "iv") eucast_rules <- function(x, col_mo = NULL, info = interactive(), rules = getOption("AMR_eucastrules", default = c("breakpoints", "expert")), verbose = FALSE, - version_breakpoints = 10.0, + version_breakpoints = 11.0, version_expertrules = 3.2, ampc_cephalosporin_resistance = NA, ...) { @@ -1168,3 +1176,26 @@ edit_rsi <- function(x, } return(track_changes) } + +#' @rdname eucast_rules +#' @export +eucast_dosage <- function(ab, administration = "iv", version_breakpoints = 11.0) { + # show used version_breakpoints number once per session (pkg_env will reload every session) + if (message_not_thrown_before(paste0("eucast_dosage_v", gsub("[^0-9]", "", version_breakpoints)), entire_session = TRUE)) { + message_("Dosages for antimicrobial drugs, as meant for ", + format_eucast_version_nr(version_breakpoints, markdown = FALSE), ". ", + font_red("This note will be shown once per session.")) + remember_thrown_message(paste0("eucast_dosage_v", gsub("[^0-9]", "", version_breakpoints)), entire_session = TRUE) + } + ab <- as.ab(ab) + out <- character(length(ab)) + for (i in seq_len(length(ab))) { + df <- data.frame(ab = ab[i], stringsAsFactors = FALSE, administration = administration) %pm>% + pm_inner_join(AMR::dosage, by = c("ab", "administration")) %pm>% + pm_mutate(txt = paste0(gsub("_", " ", type), ": ", dose_times, "x ", dose, " ", administration), perl = TRUE) + out[i] <- paste(df$txt, collapse = ", ") + } + names(out) <- ab_name(ab, language = NULL) + out[out == ""] <- NA_character_ + out +} diff --git a/R/filter_ab_class.R b/R/filter_ab_class.R index b7ae5eb1..55fe77c2 100644 --- a/R/filter_ab_class.R +++ b/R/filter_ab_class.R @@ -70,10 +70,11 @@ #' filter_aminoglycosides("R", "all") %>% #' filter_fluoroquinolones("R", "all") #' -#' # with dplyr 1.0.0 and higher (that adds 'across()'), this is equal: +#' # with dplyr 1.0.0 and higher (that adds 'across()'), this is all equal: #' # (though the row names on the first are more correct) #' example_isolates %>% filter_carbapenems("R", "all") #' example_isolates %>% filter(across(carbapenems(), ~. == "R")) +#' example_isolates %>% filter(across(carbapenems(), function(x) x == "R")) #' } #' } filter_ab_class <- function(x, @@ -129,7 +130,7 @@ filter_ab_class <- function(x, # get the columns with a group names in the chosen ab class agents <- ab_in_data[names(ab_in_data) %in% ab_reference$ab] if (length(agents) == 0) { - message_("NOTE: no antimicrobial agents of class ", ab_group, + message_("no antimicrobial agents of class ", ab_group, " found (such as ", find_ab_names(ab_class, 2), "), data left unchanged.") return(x.bak) diff --git a/R/first_isolate.R b/R/first_isolate.R index 950f345f..ee47afbd 100755 --- a/R/first_isolate.R +++ b/R/first_isolate.R @@ -27,7 +27,7 @@ #' #' Determine first (weighted) isolates of all microorganisms of every patient per episode and (if needed) per specimen type. To determine patient episodes not necessarily based on microorganisms, use [is_new_episode()] that also supports grouping with the `dplyr` package. #' @inheritSection lifecycle Stable lifecycle -#' @param x a [data.frame] containing isolates. Can be left blank when used inside `dplyr` verbs, such as [`filter()`][dplyr::filter()], [`mutate()`][dplyr::mutate()] and [`summarise()`][dplyr::summarise()]. +#' @param x a [data.frame] containing isolates. Can be left blank for automatic determination. #' @param col_date column name of the result date (or date that is was received on the lab), defaults to the first column with a date class #' @param col_patient_id column name of the unique IDs of the patients, defaults to the first column that starts with 'patient' or 'patid' (case insensitive) #' @param col_mo column name of the IDs of the microorganisms (see [as.mo()]), defaults to the first column of class [`mo`]. Values will be coerced using [as.mo()]. diff --git a/R/isolate_identifier.R b/R/isolate_identifier.R new file mode 100644 index 00000000..72a1fd12 --- /dev/null +++ b/R/isolate_identifier.R @@ -0,0 +1,128 @@ +# ==================================================================== # +# TITLE # +# Antimicrobial Resistance (AMR) Analysis for R # +# # +# SOURCE # +# https://github.com/msberends/AMR # +# # +# LICENCE # +# (c) 2018-2021 Berends MS, Luz CF et al. # +# Developed at the University of Groningen, the Netherlands, in # +# collaboration with non-profit organisations Certe Medical # +# Diagnostics & Advice, and University Medical Center Groningen. # +# # +# This R package is free software; you can freely use and distribute # +# it for both personal and commercial purposes under the terms of the # +# GNU General Public License version 2.0 (GNU GPL-2), as published by # +# the Free Software Foundation. # +# We created this package for both routine data analysis and academic # +# research and it was publicly released in the hope that it will be # +# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. # +# # +# Visit our website for the full manual and a complete tutorial about # +# how to conduct AMR analysis: https://msberends.github.io/AMR/ # +# ==================================================================== # + +#' Create identifier of an isolate +#' +#' This function will paste the microorganism code with all antimicrobial results into one string for each row in a data set. This is useful to compare isolates, e.g. between institutions or regions, when there is no genotyping available. +#' @inheritSection lifecycle Maturing lifecycle +#' @inheritParams eucast_rules +#' @param cols_ab a character vector of column names of `x`, or (a combination with) an [antibiotic selector function]([ab_class()]), such as [carbapenems()] and [aminoglysides()] +#' @export +#' @inheritSection AMR Read more on our website! +#' @examples +#' # automatic selection of microorganism and antibiotics (i.e., all columns, see ?as.rsi) +#' x <- isolate_identifier(example_isolates) +#' +#' # ignore microorganism codes, only use antimicrobial results +#' x <- isolate_identifier(example_isolates, col_mo = FALSE, cols_ab = c("AMX", "TZP", "GEN", "TOB")) +#' +#' # select antibiotics from certain antibiotic classes +#' x <- isolate_identifier(example_isolates, cols_ab = c(carbapenems(), aminoglycosides())) +isolate_identifier <- function(x, col_mo = NULL, cols_ab = NULL) { + if (is.null(col_mo)) { + col_mo <- search_type_in_df(x, "mo") + } + if (isFALSE(col_mo)) { + # is FALSE then ignore mo column + x$col_mo <- "" + col_mo <- "col_mo" + } else if (!is.null(col_mo)) { + x[, col_mo] <- paste0(as.mo(x[, col_mo, drop = TRUE]), "|") + } + + cols_ab <- deparse(substitute(cols_ab)) # support ab class selectors: isolate_identifier(x, cols_ab = carbapenems()) + if (identical(cols_ab, "NULL")) { + cols_ab <- colnames(x)[vapply(FUN.VALUE = logical(1), x, is.rsi)] + } else { + cols_ab <- tryCatch(colnames(x[, eval(parse(text = cols_ab), envir = parent.frame())]), + # tryCatch adds 4 calls, so total is -5 + error = function(e) stop_(e$message, call = -5)) + } + if (length(cols_ab) == 0) { + warning_("no columns with antimicrobial agents found", call = TRUE) + } + + out <- x[, c(col_mo, cols_ab), drop = FALSE] + out <- do.call(paste, c(out, sep = "")) + out <- gsub("NA", ".", out, fixed = TRUE) + set_clean_class(out, new_class = c("isolate_identifier", "character")) +} + +#' @method print isolate_identifier +#' @export +#' @noRd +print.isolate_identifier <- function(x, ...) { + print(as.character(x), ...) +} + +#' @method [ isolate_identifier +#' @export +#' @noRd +"[.isolate_identifier" <- function(x, ...) { + y <- NextMethod() + attributes(y) <- attributes(x) + y +} +#' @method [[ isolate_identifier +#' @export +#' @noRd +"[[.isolate_identifier" <- function(x, ...) { + y <- NextMethod() + attributes(y) <- attributes(x) + y +} +#' @method [<- isolate_identifier +#' @export +#' @noRd +"[<-.isolate_identifier" <- function(i, j, ..., value) { + y <- NextMethod() + attributes(y) <- attributes(i) + y +} +#' @method [[<- isolate_identifier +#' @export +#' @noRd +"[[<-.isolate_identifier" <- function(i, j, ..., value) { + y <- NextMethod() + attributes(y) <- attributes(i) + y +} +#' @method c isolate_identifier +#' @export +#' @noRd +c.isolate_identifier <- function(x, ...) { + y <- NextMethod() + attributes(y) <- attributes(x) + y +} + +#' @method unique isolate_identifier +#' @export +#' @noRd +unique.isolate_identifier <- function(x, incomparables = FALSE, ...) { + y <- NextMethod() + attributes(y) <- attributes(x) + y +} diff --git a/R/mdro.R b/R/mdro.R index 6f4510b6..69f83681 100755 --- a/R/mdro.R +++ b/R/mdro.R @@ -27,7 +27,7 @@ #' #' Determine which isolates are multidrug-resistant organisms (MDRO) according to international and national guidelines. #' @inheritSection lifecycle Stable lifecycle -#' @param x a [data.frame] with antibiotics columns, like `AMX` or `amox`. Can be left blank when used inside `dplyr` verbs, such as [`filter()`][dplyr::filter()], [`mutate()`][dplyr::mutate()] and [`summarise()`][dplyr::summarise()]. +#' @param x a [data.frame] with antibiotics columns, like `AMX` or `amox`. Can be left blank for automatic determination. #' @param guideline a specific guideline to follow. When left empty, the publication by Magiorakos *et al.* (2012, Clinical Microbiology and Infection) will be followed, please see *Details*. #' @inheritParams eucast_rules #' @param pct_required_classes minimal required percentage of antimicrobial classes that must be available per isolate, rounded down. For example, with the default guideline, 17 antimicrobial classes must be available for *S. aureus*. Setting this `pct_required_classes` argument to `0.5` (default) means that for every *S. aureus* isolate at least 8 different classes must be available. Any lower number of available classes will return `NA` for that isolate. diff --git a/R/mo.R b/R/mo.R index 2b24c34c..7bc2a449 100755 --- a/R/mo.R +++ b/R/mo.R @@ -756,7 +756,7 @@ exec_as.mo <- function(x, x[i] <- lookup(mo == "B_STRPT_HAEM", uncertainty = -1) next } - # CoNS/CoPS in different languages (support for German, Dutch, Spanish, Portuguese) ---- + # CoNS/CoPS in different languages (support for German, Dutch, Spanish, Portuguese) if (x_backup_without_spp[i] %like_case% "[ck]oagulas[ea] negatie?[vf]" | x_trimmed[i] %like_case% "[ck]oagulas[ea] negatie?[vf]" | x_backup_without_spp[i] %like_case% "[ck]o?ns[^a-z]?$") { @@ -841,8 +841,17 @@ exec_as.mo <- function(x, x[i] <- lookup(fullname == "Streptococcus pneumoniae", uncertainty = -1) next } - # } - + + if (x_backup[i] %in% pkg_env$mo_failed) { + # previously failed already in this session ---- + # (at this point the latest reference_df has also be checked) + x[i] <- lookup(mo == "UNKNOWN") + if (initial_search == TRUE) { + failures <- c(failures, x_backup[i]) + } + next + } + # NOW RUN THROUGH DIFFERENT PREVALENCE LEVELS check_per_prevalence <- function(data_to_check, data.old_to_check, @@ -1397,6 +1406,7 @@ exec_as.mo <- function(x, failures <- failures[!failures %in% c(NA, NULL, NaN)] if (length(failures) > 0 & initial_search == TRUE) { pkg_env$mo_failures <- sort(unique(failures)) + pkg_env$mo_failed <- c(pkg_env$mo_failed, pkg_env$mo_failures) plural <- c("value", "it", "was") if (pm_n_distinct(failures) > 1) { plural <- c("values", "them", "were") @@ -1412,7 +1422,7 @@ exec_as.mo <- function(x, } msg <- paste0(msg, ".\nUse mo_failures() to review ", plural[2], ". Edit the `allow_uncertain` argument if needed (see ?as.mo).\n", - "You can also use your own reference data, e.g.:\n", + "You can also use your own reference data with set_mo_source() or directly, e.g.:\n", ' as.mo("mycode", reference_df = data.frame(own = "mycode", mo = "', MO_lookup$mo[match("Escherichia coli", MO_lookup$fullname)], '"))\n', ' mo_name("mycode", reference_df = data.frame(own = "mycode", mo = "', MO_lookup$mo[match("Escherichia coli", MO_lookup$fullname)], '"))\n') warning_(paste0("\n", msg), @@ -1430,7 +1440,7 @@ exec_as.mo <- function(x, plural <- c("s", "them", "were") } msg <- paste0("Translation to ", nr2char(length(uncertainties$input)), " microorganism", plural[1], - " ", plural[3], " guessed with uncertainty. Use mo_uncertainties() to review ", plural[2], ".") + " was guessed with uncertainty. Use mo_uncertainties() to review ", plural[2], ".") message_(msg) } @@ -1960,12 +1970,12 @@ replace_old_mo_codes <- function(x, property) { x[which(!is.na(matched))] <- mo_new[which(!is.na(matched))] n_matched <- length(matched[!is.na(matched)]) if (property != "mo") { - message_(font_blue("NOTE: The input contained old microbial codes (from previous package versions). Please update your MO codes with as.mo().")) + message_(font_blue("The input contained old microbial codes (from previous package versions). Please update your MO codes with as.mo().")) } else { if (n_matched == 1) { - message_(font_blue("NOTE: 1 old microbial code (from previous package versions) was updated to a current used MO code.")) + message_(font_blue("1 old microbial code (from previous package versions) was updated to a current used MO code.")) } else { - message_(font_blue("NOTE:", n_matched, "old microbial codes (from previous package versions) were updated to current used MO codes.")) + message_(font_blue(n_matched, "old microbial codes (from previous package versions) were updated to current used MO codes.")) } } } diff --git a/R/mo_matching_score.R b/R/mo_matching_score.R index 970812d4..fe7b147c 100755 --- a/R/mo_matching_score.R +++ b/R/mo_matching_score.R @@ -33,21 +33,23 @@ #' @section Matching score for microorganisms: #' With ambiguous user input in [as.mo()] and all the [`mo_*`][mo_property()] functions, the returned results are chosen based on their matching score using [mo_matching_score()]. This matching score \eqn{m}, is calculated as: #' -#' \deqn{m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \textrm{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}}{m(x, n) = ( l_n * min(l_n, lev(x, n) ) ) / ( l_n * p_n * k_n )} +#' \ifelse{latex}{\deqn{m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \textrm{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}}}{\ifelse{html}{\figure{mo_matching_score.png}{options: width="300px" alt="mo matching score"}}{m(x, n) = ( l_n * min(l_n, lev(x, n) ) ) / ( l_n * p_n * k_n )}} #' #' where: #' -#' * \eqn{x} is the user input; -#' * \eqn{n} is a taxonomic name (genus, species, and subspecies); -#' * \eqn{l_n}{l_n} is the length of \eqn{n}; -#' * lev is the [Levenshtein distance function](https://en.wikipedia.org/wiki/Levenshtein_distance), which counts any insertion, deletion and substitution as 1 that is needed to change \eqn{x} into \eqn{n}; -#' * \eqn{p_n}{p_n} is the human pathogenic prevalence group of \eqn{n}, as described below; -#' * \eqn{k_n}{p_n} is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5. +#' * \ifelse{html}{\out{x is the user input;}}{\eqn{x} is the user input;} +#' * \ifelse{html}{\out{n is a taxonomic name (genus, species, and subspecies);}}{\eqn{n} is a taxonomic name (genus, species, and subspecies);} +#' * \ifelse{html}{\out{ln is the length of n;}}{l_n is the length of \eqn{n};} +#' * \ifelse{html}{\out{lev is the Levenshtein distance function, which counts any insertion, deletion and substitution as 1 that is needed to change x into n;}}{lev is the Levenshtein distance function, which counts any insertion, deletion and substitution as 1 that is needed to change \eqn{x} into \eqn{n};} +#' * \ifelse{html}{\out{pn is the human pathogenic prevalence group of n, as described below;}}{p_n is the human pathogenic prevalence group of \eqn{n}, as described below;} +#' * \ifelse{html}{\out{kn is the taxonomic kingdom of n, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}}{l_n is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.} #' #' The grouping into human pathogenic prevalence (\eqn{p}) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. **Group 1** (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is *Enterococcus*, *Staphylococcus* or *Streptococcus*. This group consequently contains all common Gram-negative bacteria, such as *Pseudomonas* and *Legionella* and all species within the order Enterobacterales. **Group 2** consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is *Absidia*, *Acremonium*, *Actinotignum*, *Alternaria*, *Anaerosalibacter*, *Apophysomyces*, *Arachnia*, *Aspergillus*, *Aureobacterium*, *Aureobasidium*, *Bacteroides*, *Basidiobolus*, *Beauveria*, *Blastocystis*, *Branhamella*, *Calymmatobacterium*, *Candida*, *Capnocytophaga*, *Catabacter*, *Chaetomium*, *Chryseobacterium*, *Chryseomonas*, *Chrysonilia*, *Cladophialophora*, *Cladosporium*, *Conidiobolus*, *Cryptococcus*, *Curvularia*, *Exophiala*, *Exserohilum*, *Flavobacterium*, *Fonsecaea*, *Fusarium*, *Fusobacterium*, *Hendersonula*, *Hypomyces*, *Koserella*, *Lelliottia*, *Leptosphaeria*, *Leptotrichia*, *Malassezia*, *Malbranchea*, *Mortierella*, *Mucor*, *Mycocentrospora*, *Mycoplasma*, *Nectria*, *Ochroconis*, *Oidiodendron*, *Phoma*, *Piedraia*, *Pithomyces*, *Pityrosporum*, *Prevotella*,\\*Pseudallescheria*, *Rhizomucor*, *Rhizopus*, *Rhodotorula*, *Scolecobasidium*, *Scopulariopsis*, *Scytalidium*,*Sporobolomyces*, *Stachybotrys*, *Stomatococcus*, *Treponema*, *Trichoderma*, *Trichophyton*, *Trichosporon*, *Tritirachium* or *Ureaplasma*. **Group 3** consists of all other microorganisms. #' #' All matches are sorted descending on their matching score and for all user input values, the top match will be returned. This will lead to the effect that e.g., `"E. coli"` will return the microbial ID of *Escherichia coli* (\eqn{m = `r round(mo_matching_score("E. coli", "Escherichia coli"), 3)`}, a highly prevalent microorganism found in humans) and not *Entamoeba coli* (\eqn{m = `r round(mo_matching_score("E. coli", "Entamoeba coli"), 3)`}, a less prevalent microorganism in humans), although the latter would alphabetically come first. #' @export +#' @inheritSection AMR Reference data publicly available +#' @inheritSection AMR Read more on our website! #' @examples #' as.mo("E. coli") #' mo_uncertainties() diff --git a/R/mo_property.R b/R/mo_property.R index 33cc7ba0..a94da54c 100755 --- a/R/mo_property.R +++ b/R/mo_property.R @@ -27,7 +27,7 @@ #' #' Use these functions to return a specific property of a microorganism based on the latest accepted taxonomy. All input values will be evaluated internally with [as.mo()], which makes it possible to use microbial abbreviations, codes and names as input. Please see *Examples*. #' @inheritSection lifecycle Stable lifecycle -#' @param x any character (vector) that can be coerced to a valid microorganism code with [as.mo()]. Can be left blank for auto-guessing the column containing microorganism codes when used inside `dplyr` verbs, such as [`filter()`][dplyr::filter()], [`mutate()`][dplyr::mutate()] and [`summarise()`][dplyr::summarise()], please see *Examples*. +#' @param x any character (vector) that can be coerced to a valid microorganism code with [as.mo()]. Can be left blank for auto-guessing the column containing microorganism codes if used in a data set, please see *Examples*. #' @param property one of the column names of the [microorganisms] data set: `r paste0('"``', colnames(microorganisms), '\``"', collapse = ", ")`, or must be `"shortname"` #' @param language language of the returned text, defaults to system language (see [get_locale()]) and can be overwritten by setting the option `AMR_locale`, e.g. `options(AMR_locale = "de")`, see [translate]. Also used to translate text like "no growth". Use `language = NULL` or `language = ""` to prevent translation. #' @param ... other arguments passed on to [as.mo()], such as 'allow_uncertain' and 'ignore_pattern' @@ -44,6 +44,8 @@ #' #' The Gram stain - [mo_gramstain()] - will be determined based on the taxonomic kingdom and phylum. According to Cavalier-Smith (2002, [PMID 11837318](https://pubmed.ncbi.nlm.nih.gov/11837318)), who defined subkingdoms Negibacteria and Posibacteria, only these phyla are Posibacteria: Actinobacteria, Chloroflexi, Firmicutes and Tenericutes. These bacteria are considered Gram-positive - all other bacteria are considered Gram-negative. Species outside the kingdom of Bacteria will return a value `NA`. Functions [mo_is_gram_negative()] and [mo_is_gram_positive()] always return `TRUE` or `FALSE` (except when the input is `NA` or the MO code is `UNKNOWN`), thus always return `FALSE` for species outside the taxonomic kingdom of Bacteria. #' +#' Determination of yeasts - [mo_is_yeast()] - will be based on the taxonomic phylum, class and order. Budding yeasts are true fungi of the phylum Ascomycetes, class Saccharomycetes (also called Hemiascomycetes). The true yeasts are separated into one main order Saccharomycetales. For all microorganisms that are in one of those two groups, the function will return `TRUE`. It returns `FALSE` for all other taxonomic entries. +#' #' Intrinsic resistance - [mo_is_intrinsic_resistant()] - will be determined based on the [intrinsic_resistant] data set, which is based on `r format_eucast_version_nr(3.2)`. The [mo_is_intrinsic_resistant()] can be vectorised over arguments `x` (input for microorganisms) and over `ab` (input for antibiotics). #' #' All output will be [translate]d where possible. @@ -145,6 +147,8 @@ #' #' # other -------------------------------------------------------------------- #' +#' mo_is_yeast(c("Candida", "E. coli")) # TRUE, FALSE +#' #' # gram stains and intrinsic resistance can also be used as a filter in dplyr verbs #' if (require("dplyr")) { #' example_isolates %>% @@ -331,7 +335,10 @@ mo_type <- function(x, language = get_locale(), ...) { meet_criteria(x, allow_NA = TRUE) meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE) - translate_AMR(mo_validate(x = x, property = "kingdom", language = language, ...), language = language, only_unknown = FALSE) + x.mo <- as.mo(x, language = language, ...) + out <- mo_kingdom(x.mo, language = NULL) + out[which(mo_is_yeast(x.mo))] <- "Yeasts" + translate_AMR(out, language = language, only_unknown = FALSE) } #' @rdname mo_property @@ -410,6 +417,33 @@ mo_is_gram_positive <- function(x, language = get_locale(), ...) { out } +#' @rdname mo_property +#' @export +mo_is_yeast <- function(x, language = get_locale(), ...) { + if (missing(x)) { + # this tries to find the data and an column + x <- find_mo_col(fn = "mo_is_yeast") + } + meet_criteria(x, allow_NA = TRUE) + meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE) + + x.mo <- as.mo(x, language = language, ...) + metadata <- get_mo_failures_uncertainties_renamed() + + x.kingdom <- mo_kingdom(x.mo, language = NULL) + x.phylum <- mo_phylum(x.mo, language = NULL) + x.class <- mo_class(x.mo, language = NULL) + x.order <- mo_order(x.mo, language = NULL) + + load_mo_failures_uncertainties_renamed(metadata) + + out <- rep(FALSE, length(x)) + out[x.kingdom == "Fungi" & + ((x.phylum == "Ascomycetes" & x.class == "Saccharomycetes") | x.order == "Saccharomycetales")] <- TRUE + out[x.mo %in% c(NA_character_, "UNKNOWN")] <- NA + out +} + #' @rdname mo_property #' @export mo_is_intrinsic_resistant <- function(x, ab, language = get_locale(), ...) { diff --git a/R/sysdata.rda b/R/sysdata.rda index 1ad11c86..9c6d291d 100644 Binary files a/R/sysdata.rda and b/R/sysdata.rda differ diff --git a/R/zzz.R b/R/zzz.R index 4f75c05f..7ed13808 100755 --- a/R/zzz.R +++ b/R/zzz.R @@ -25,6 +25,7 @@ # set up package environment, used by numerous AMR functions pkg_env <- new.env(hash = FALSE) +pkg_env$mo_failed <- character(0) .onLoad <- function(libname, pkgname) { diff --git a/_pkgdown.yml b/_pkgdown.yml index 383ce99d..8def1198 100644 --- a/_pkgdown.yml +++ b/_pkgdown.yml @@ -99,18 +99,19 @@ reference: for more information about how to work with functions in this package. contents: - "`AMR`" + - "`example_isolates`" + - "`microorganisms`" + - "`microorganisms.codes`" + - "`microorganisms.old`" + - "`antibiotics`" + - "`intrinsic_resistant`" + - "`dosage`" - "`catalogue_of_life`" - "`catalogue_of_life_version`" - "`WHOCC`" - "`lifecycle`" - - "`microorganisms`" - - "`antibiotics`" - - "`intrinsic_resistant`" - - "`example_isolates`" - "`example_isolates_unclean`" - "`rsi_translation`" - - "`microorganisms.codes`" - - "`microorganisms.old`" - "`WHONET`" - title: "Preparing data: microorganisms" @@ -143,6 +144,7 @@ reference: - "`as.disk`" - "`eucast_rules`" - "`plot`" + - "`isolate_identifier`" - title: "Analysing data: antimicrobial resistance" desc: > diff --git a/data-raw/AMR_1.5.0.tar.gz b/data-raw/AMR_1.5.0.9000.tar.gz similarity index 70% rename from data-raw/AMR_1.5.0.tar.gz rename to data-raw/AMR_1.5.0.9000.tar.gz index d987293d..0217ff26 100644 Binary files a/data-raw/AMR_1.5.0.tar.gz and b/data-raw/AMR_1.5.0.9000.tar.gz differ diff --git a/data-raw/Dosages_v_11.0_Breakpoint_Tables.xlsx b/data-raw/Dosages_v_11.0_Breakpoint_Tables.xlsx new file mode 100644 index 00000000..35042aa3 Binary files /dev/null and b/data-raw/Dosages_v_11.0_Breakpoint_Tables.xlsx differ diff --git a/data-raw/ab.md5 b/data-raw/ab.md5 index d4b49898..a54d8a40 100644 --- a/data-raw/ab.md5 +++ b/data-raw/ab.md5 @@ -1 +1 @@ -a30faa0e4475d440d1bb8e44e6857062 +fa68ab044001078f290218a7de6cc5c4 diff --git a/data-raw/antibiotics.dta b/data-raw/antibiotics.dta index e3ea1e94..98ea22d2 100644 Binary files a/data-raw/antibiotics.dta and b/data-raw/antibiotics.dta differ diff --git a/data-raw/antibiotics.rds b/data-raw/antibiotics.rds index f61a90bc..89143ae4 100644 Binary files a/data-raw/antibiotics.rds and b/data-raw/antibiotics.rds differ diff --git a/data-raw/antibiotics.sas b/data-raw/antibiotics.sas index 9d85758e..a7acfc43 100644 Binary files a/data-raw/antibiotics.sas and b/data-raw/antibiotics.sas differ diff --git a/data-raw/antibiotics.sav b/data-raw/antibiotics.sav index 33820475..668ddb04 100644 Binary files a/data-raw/antibiotics.sav and b/data-raw/antibiotics.sav differ diff --git a/data-raw/antibiotics.txt b/data-raw/antibiotics.txt index 23d0fdc4..f9ba3ce5 100644 --- a/data-raw/antibiotics.txt +++ b/data-raw/antibiotics.txt @@ -37,6 +37,8 @@ "BEK" 439318 "Bekanamycin" "Aminoglycosides" "" "c(\"aminodeoxykanamycin\", \"becanamicina\", \"bekanamycin\", \"bekanamycine\", \"bekanamycinum\", \"nebramycin v\")" "character(0)" "BNB" "J01CE08" "Benzathine benzylpenicillin" "Beta-lactams/penicillins" "Beta-lactam antibacterials, penicillins" "Beta-lactamase sensitive penicillins" "" "" 3.6 "g" "" "BNP" "J01CE10" 64725 "Benzathine phenoxymethylpenicillin" "Beta-lactams/penicillins" "Beta-lactam antibacterials, penicillins" "Beta-lactamase sensitive penicillins" "" "c(\"bicillin v\", \"biphecillin\")" 2 "g" "character(0)" +"PEN" "J01CE01" 5904 "Benzylpenicillin" "Beta-lactams/penicillins" "Combinations of antibacterials" "Combinations of antibacterials" "c(\"bepe\", \"pen\", \"peni\", \"peni g\", \"penicillin\", \"penicillin g\", \"pg\")" "c(\"abbocillin\", \"ayercillin\", \"bencilpenicilina\", \"benzopenicillin\", \"benzyl penicillin\", \"benzylpenicillin\", \"benzylpenicillin g\", \"benzylpenicilline\", \"benzylpenicillinum\", \"bicillin\", \"cillora\", \"cilloral\", \"cilopen\", \"compocillin g\", \"cosmopen\", \"dropcillin\", \"free penicillin g\", \"free penicillin ii\", \"galofak\", \"gelacillin\", \"liquacillin\", \"megacillin\", \"pencillin g\", \"penicillin\", \"penicilling\", \"pentids\", \"permapen\", \"pfizerpen\", \"pfizerpen g\", \"pharmacillin\", \"pradupen\", \"specilline g\", \"ursopen\" +)" 3.6 "g" "3913-1" "BES" 10178705 "Besifloxacin" "Quinolones" "" "besifloxacin" "character(0)" "BIA" 71339 "Biapenem" "Carbapenems" "" "c(\"biapenem\", \"biapenern\", \"bipenem\", \"omegacin\")" "character(0)" "BCZ" 65807 "Bicyclomycin (Bicozamycin)" "Other antibacterials" "" "c(\"aizumycin\", \"bacfeed\", \"bacteron\", \"bicozamicina\", \"bicozamycin\", \"bicozamycine\", \"bicozamycinum\")" "character(0)" @@ -328,8 +330,6 @@ "PAZ" "J01MA18" 65957 "Pazufloxacin" "Quinolones" "Quinolone antibacterials" "Fluoroquinolones" "" "c(\"pazufloxacin\", \"pazufloxacine\", \"pazufloxacino\", \"pazufloxacinum\")" 1 "g" "character(0)" "PEF" "J01MA03" 51081 "Pefloxacin" "Quinolones" "Quinolone antibacterials" "Fluoroquinolones" "c(\"\", \"pefl\")" "c(\"abactal\", \"labocton\", \"pefloxacin\", \"pefloxacine\", \"pefloxacino\", \"pefloxacinum\", \"perfloxacin\", \"silver pefloxacin\")" 0.8 "g" 0.8 "g" "3906-5" "PNM" "J01CE06" 10250769 "Penamecillin" "Beta-lactams/penicillins" "Beta-lactam antibacterials, penicillins" "Beta-lactamase sensitive penicillins" "" "c(\"hydroxymethyl\", \"penamecilina\", \"penamecillin\", \"penamecillina\", \"penamecilline\", \"penamecillinum\")" 1.05 "g" "character(0)" -"PEN" "J01CE01" 5904 "Benzylpenicillin" "Beta-lactams/penicillins" "Combinations of antibacterials" "Combinations of antibacterials" "c(\"bepe\", \"pen\", \"peni\", \"peni g\", \"penicillin\", \"penicillin g\", \"pg\")" "c(\"abbocillin\", \"ayercillin\", \"bencilpenicilina\", \"benzopenicillin\", \"benzyl penicillin\", \"benzylpenicillin\", \"benzylpenicillin g\", \"benzylpenicilline\", \"benzylpenicillinum\", \"bicillin\", \"cillora\", \"cilloral\", \"cilopen\", \"compocillin g\", \"cosmopen\", \"dropcillin\", \"free penicillin g\", \"free penicillin ii\", \"galofak\", \"gelacillin\", \"liquacillin\", \"megacillin\", \"pencillin g\", \"penicillin\", \"penicilling\", \"pentids\", \"permapen\", \"pfizerpen\", \"pfizerpen g\", \"pharmacillin\", \"pradupen\", \"specilline g\", \"ursopen\" -)" 3.6 "g" "3913-1" "PNO" "Penicillin/novobiocin" "Beta-lactams/penicillins" "" "" "" "PSU" "Penicillin/sulbactam" "Beta-lactams/penicillins" "" "" "" "PNM1" "J01AA10" 54686187 "Penimepicycline" "Tetracyclines" "Tetracyclines" "Tetracyclines" "" "c(\"duamine\", \"hydrocycline\", \"penetracyne\", \"penimepiciclina\", \"penimepicycline\", \"penimepicyclinum\")" "character(0)" @@ -354,6 +354,7 @@ "POS" "J02AC04" 468595 "Posaconazole" "Antifungals/antimycotics" "Antimycotics for systemic use" "Triazole derivatives" "posa" "c(\"noxafil\", \"posaconazole\", \"posaconazole sp\", \"posconazole\")" 0.3 "g" 0.3 "g" "c(\"53731-6\", \"80545-7\")" "PRA" 9802884 "Pradofloxacin" "Quinolones" "" "pradofloxacin" "character(0)" "PRX" 71455 "Premafloxacin" "Quinolones" "" "premafloxacin" "character(0)" +"PMD" "J04AK08" 456199 "Pretomanid" "Antimycobacterials" "Drugs for treatment of tuberculosis" "Other drugs for treatment of tuberculosis" "" "" "" "PRM" 6446787 "Primycin" "Macrolides/lincosamides" "" "" "" "PRI" "J01FG01" 11979535 "Pristinamycin" "Macrolides/lincosamides" "Macrolides, lincosamides and streptogramins" "Streptogramins" "c(\"\", \"pris\")" "c(\"eskalin v\", \"mikamycin\", \"mikamycine\", \"mikamycinum\", \"ostreogrycinum\", \"pristinamycine\", \"pristinamycinum\", \"stafac\", \"stafytracine\", \"staphylomycin\", \"starfac\", \"streptogramin\", \"vernamycin\", \"virgimycin\", \"virgimycine\", \"virginiamycina\", \"virginiamycine\", \"virginiamycinum\")" 2 "g" "character(0)" "PRB" "J01CE09" 5903 "Procaine benzylpenicillin" "Beta-lactams/penicillins" "Beta-lactam antibacterials, penicillins" "Beta-lactamase sensitive penicillins" "" "c(\"depocillin\", \"duphapen\", \"hostacillin\", \"hydracillin\", \"jenacillin o\", \"nopcaine\", \"penicillin procaine\", \"retardillin\", \"vetspen\", \"vitablend\")" 0.6 "g" "character(0)" diff --git a/data-raw/antibiotics.xlsx b/data-raw/antibiotics.xlsx index 95cfcbd1..7aa01de4 100644 Binary files a/data-raw/antibiotics.xlsx and b/data-raw/antibiotics.xlsx differ diff --git a/data-raw/eucast_rules.tsv b/data-raw/eucast_rules.tsv index 880522e3..9251dc55 100644 --- a/data-raw/eucast_rules.tsv +++ b/data-raw/eucast_rules.tsv @@ -115,6 +115,115 @@ genus_species is Kingella kingae TCY R DOX R Kingella kingae Breakpoints 10 genus_species is Burkholderia pseudomallei TCY S DOX S Burkholderia pseudomallei Breakpoints 10 genus_species is Burkholderia pseudomallei TCY I DOX I Burkholderia pseudomallei Breakpoints 10 genus_species is Burkholderia pseudomallei TCY R DOX R Burkholderia pseudomallei Breakpoints 10 +order is Enterobacterales AMP S AMX S Enterobacterales (Order) Breakpoints 11 +order is Enterobacterales AMP I AMX I Enterobacterales (Order) Breakpoints 11 +order is Enterobacterales AMP R AMX R Enterobacterales (Order) Breakpoints 11 +genus is Staphylococcus PEN, FOX S AMP, AMX, PIP, TIC S Staphylococcus Breakpoints 11 +genus is Staphylococcus PEN, FOX R, S OXA, FLC S Staphylococcus Breakpoints 11 +genus is Staphylococcus FOX R all_betalactams R Staphylococcus Breakpoints 11 +genus_species is Staphylococcus saprophyticus AMP S AMX, AMC, PIP, TZP S Staphylococcus Breakpoints 11 +genus is Staphylococcus FOX S carbapenems, cephalosporins_except_CAZ S Staphylococcus Breakpoints 11 +genus is Staphylococcus FOX I carbapenems, cephalosporins_except_CAZ I Staphylococcus Breakpoints 11 +genus is Staphylococcus FOX R carbapenems, cephalosporins_except_CAZ R Staphylococcus Breakpoints 11 +genus is Staphylococcus NOR S CIP, LVX, MFX, OFX S Staphylococcus Breakpoints 11 +genus is Staphylococcus ERY S AZM, CLR, RXT S Staphylococcus Breakpoints 11 +genus is Staphylococcus ERY I AZM, CLR, RXT I Staphylococcus Breakpoints 11 +genus is Staphylococcus ERY R AZM, CLR, RXT R Staphylococcus Breakpoints 11 +genus is Staphylococcus TCY S DOX, MNO S Staphylococcus Breakpoints 11 +genus is Enterococcus AMP S AMX, AMC, PIP, TZP S Enterococcus Breakpoints 11 +genus is Enterococcus AMP I AMX, AMC, PIP, TZP I Enterococcus Breakpoints 11 +genus is Enterococcus AMP R AMX, AMC, PIP, TZP R Enterococcus Breakpoints 11 +genus is Enterococcus NOR S CIP, LVX S Enterococcus Breakpoints 11 +genus is Enterococcus NOR I CIP, LVX I Enterococcus Breakpoints 11 +genus is Enterococcus NOR R CIP, LVX R Enterococcus Breakpoints 11 +genus_species one_of Streptococcus group A, Streptococcus group B, Streptococcus group C, Streptococcus group G PEN S aminopenicillins, ureidopenicillins, cephalosporins_except_CAZ, carbapenems, FLC, AMC S Streptococcus groups A, B, C, G Breakpoints 11 +genus_species like Streptococcus group A, Streptococcus group B, Streptococcus group C, Streptococcus group G PEN I aminopenicillins, ureidopenicillins, cephalosporins_except_CAZ, carbapenems, FLC, AMC I Streptococcus groups A, B, C, G Breakpoints 11 +genus_species like Streptococcus group A, Streptococcus group B, Streptococcus group C, Streptococcus group G PEN R aminopenicillins, ureidopenicillins, cephalosporins_except_CAZ, carbapenems, FLC, AMC R Streptococcus groups A, B, C, G Breakpoints 11 +genus_species like Streptococcus group A, Streptococcus group B, Streptococcus group C, Streptococcus group G NOR S MFX S Streptococcus groups A, B, C, G Breakpoints 11 +genus_species like Streptococcus group A, Streptococcus group B, Streptococcus group C, Streptococcus group G NOR S LVX I Streptococcus groups A, B, C, G Breakpoints 11 +genus_species like Streptococcus group A, Streptococcus group B, Streptococcus group C, Streptococcus group G ERY S AZM, CLR, RXT S Streptococcus groups A, B, C, G Breakpoints 11 +genus_species like Streptococcus group A, Streptococcus group B, Streptococcus group C, Streptococcus group G ERY I AZM, CLR, RXT I Streptococcus groups A, B, C, G Breakpoints 11 +genus_species like Streptococcus group A, Streptococcus group B, Streptococcus group C, Streptococcus group G ERY R AZM, CLR, RXT R Streptococcus groups A, B, C, G Breakpoints 11 +genus_species like Streptococcus group A, Streptococcus group B, Streptococcus group C, Streptococcus group G TCY S DOX, MNO S Streptococcus groups A, B, C, G Breakpoints 11 +genus_species is Streptococcus pneumoniae PEN S AMP, AMX, AMC, PIP, TZP S Streptococcus pneumoniae Breakpoints 11 +genus_species is Streptococcus pneumoniae AMP S AMX, AMC, PIP, TZP S Streptococcus pneumoniae Breakpoints 11 +genus_species is Streptococcus pneumoniae AMP I AMX, AMC, PIP, TZP I Streptococcus pneumoniae Breakpoints 11 +genus_species is Streptococcus pneumoniae AMP R AMX, AMC, PIP, TZP R Streptococcus pneumoniae Breakpoints 11 +genus_species is Streptococcus pneumoniae NOR S MFX S Streptococcus pneumoniae Breakpoints 11 +genus_species is Streptococcus pneumoniae NOR S LVX I Streptococcus pneumoniae Breakpoints 11 +genus_species is Streptococcus pneumoniae ERY S AZM, CLR, RXT S Streptococcus pneumoniae Breakpoints 11 +genus_species is Streptococcus pneumoniae ERY I AZM, CLR, RXT I Streptococcus pneumoniae Breakpoints 11 +genus_species is Streptococcus pneumoniae ERY R AZM, CLR, RXT R Streptococcus pneumoniae Breakpoints 11 +genus_species is Streptococcus pneumoniae TCY S DOX, MNO S Streptococcus pneumoniae Breakpoints 11 +genus_species like ^Streptococcus (anginosus|australis|bovis|constellatus|cristatus|equinus|gallolyticus|gordonii|infantarius|infantis|intermedius|mitis|mutans|oligofermentans|oralis|parasanguinis|peroris|pseudopneumoniae|salivarius|sanguinis|sinensis|sobrinus|thermophilus|vestibularis|viridans)$ PEN S AMP, AMX, AMC, PIP, TZP S Viridans group streptococci Breakpoints 11 +genus_species like ^Streptococcus (anginosus|australis|bovis|constellatus|cristatus|equinus|gallolyticus|gordonii|infantarius|infantis|intermedius|mitis|mutans|oligofermentans|oralis|parasanguinis|peroris|pseudopneumoniae|salivarius|sanguinis|sinensis|sobrinus|thermophilus|vestibularis|viridans)$ AMP S AMX, AMC, PIP, TZP S Viridans group streptococci Breakpoints 11 +genus_species like ^Streptococcus (anginosus|australis|bovis|constellatus|cristatus|equinus|gallolyticus|gordonii|infantarius|infantis|intermedius|mitis|mutans|oligofermentans|oralis|parasanguinis|peroris|pseudopneumoniae|salivarius|sanguinis|sinensis|sobrinus|thermophilus|vestibularis|viridans)$ AMP I AMX, AMC, PIP, TZP I Viridans group streptococci Breakpoints 11 +genus_species like ^Streptococcus (anginosus|australis|bovis|constellatus|cristatus|equinus|gallolyticus|gordonii|infantarius|infantis|intermedius|mitis|mutans|oligofermentans|oralis|parasanguinis|peroris|pseudopneumoniae|salivarius|sanguinis|sinensis|sobrinus|thermophilus|vestibularis|viridans)$ AMP R AMX, AMC, PIP, TZP R Viridans group streptococci Breakpoints 11 +genus_species is Haemophilus influenzae AMP S AMX, PIP S Haemophilus influenzae Breakpoints 11 +genus_species is Haemophilus influenzae AMP I AMX, PIP I Haemophilus influenzae Breakpoints 11 +genus_species is Haemophilus influenzae AMP R AMX, PIP R Haemophilus influenzae Breakpoints 11 +genus_species is Haemophilus influenzae PEN S AMP, AMX, AMC, PIP, TZP S Haemophilus influenzae Breakpoints 11 +genus_species is Haemophilus influenzae AMC S TZP S Haemophilus influenzae Breakpoints 11 +genus_species is Haemophilus influenzae AMC I TZP I Haemophilus influenzae Breakpoints 11 +genus_species is Haemophilus influenzae AMC R TZP R Haemophilus influenzae Breakpoints 11 +genus_species is Haemophilus influenzae NAL S CIP, LVX, MFX, OFX S Haemophilus influenzae Breakpoints 11 +genus_species is Haemophilus influenzae TCY S DOX, MNO S Haemophilus influenzae Breakpoints 11 +genus_species is Moraxella catarrhalis AMC S TZP S Moraxella catarrhalis Breakpoints 11 +genus_species is Moraxella catarrhalis AMC I TZP I Moraxella catarrhalis Breakpoints 11 +genus_species is Moraxella catarrhalis AMC R TZP R Moraxella catarrhalis Breakpoints 11 +genus_species is Moraxella catarrhalis NAL S CIP, LVX, MFX, OFX S Moraxella catarrhalis Breakpoints 11 +genus_species is Moraxella catarrhalis ERY S AZM, CLR, RXT S Moraxella catarrhalis Breakpoints 11 +genus_species is Moraxella catarrhalis ERY I AZM, CLR, RXT I Moraxella catarrhalis Breakpoints 11 +genus_species is Moraxella catarrhalis ERY R AZM, CLR, RXT R Moraxella catarrhalis Breakpoints 11 +genus_species is Moraxella catarrhalis TCY S DOX, MNO S Moraxella catarrhalis Breakpoints 11 +genus one_of Actinomyces, Bifidobacterium, Clostridium, Cutibacterium, Eggerthella, Eubacterium, Lactobacillus, Propionibacterium PEN S AMP, AMX, PIP, TZP, TIC S Anaerobic Gram-positives Breakpoints 11 +genus one_of Actinomyces, Bifidobacterium, Clostridium, Cutibacterium, Eggerthella, Eubacterium, Lactobacillus, Propionibacterium PEN I AMP, AMX, PIP, TZP, TIC I Anaerobic Gram-positives Breakpoints 11 +genus one_of Actinomyces, Bifidobacterium, Clostridium, Cutibacterium, Eggerthella, Eubacterium, Lactobacillus, Propionibacterium PEN R AMP, AMX, PIP, TZP, TIC R Anaerobic Gram-positives Breakpoints 11 +genus one_of Bacteroides, Bilophila , Fusobacterium, Mobiluncus, Porphyromonas, Prevotella PEN S AMP, AMX, PIP, TZP, TIC S Anaerobic Gram-negatives Breakpoints 11 +genus one_of Bacteroides, Bilophila , Fusobacterium, Mobiluncus, Porphyromonas, Prevotella PEN I AMP, AMX, PIP, TZP, TIC I Anaerobic Gram-negatives Breakpoints 11 +genus one_of Bacteroides, Bilophila , Fusobacterium, Mobiluncus, Porphyromonas, Prevotella PEN R AMP, AMX, PIP, TZP, TIC R Anaerobic Gram-negatives Breakpoints 11 +genus_species is Pasteurella multocida PEN S AMP, AMX S Pasteurella multocida Breakpoints 11 +genus_species is Pasteurella multocida PEN I AMP, AMX I Pasteurella multocida Breakpoints 11 +genus_species is Pasteurella multocida PEN R AMP, AMX R Pasteurella multocida Breakpoints 11 +genus_species is Campylobacter coli ERY S AZM, CLR S Campylobacter coli Breakpoints 11 +genus_species is Campylobacter coli ERY I AZM, CLR I Campylobacter coli Breakpoints 11 +genus_species is Campylobacter coli ERY R AZM, CLR R Campylobacter coli Breakpoints 11 +genus_species is Campylobacter coli TCY S DOX S Campylobacter coli Breakpoints 11 +genus_species is Campylobacter coli TCY I DOX I Campylobacter coli Breakpoints 11 +genus_species is Campylobacter coli TCY R DOX R Campylobacter coli Breakpoints 11 +genus_species is Campylobacter jejuni ERY S AZM, CLR S Campylobacter jejuni Breakpoints 11 +genus_species is Campylobacter jejuni ERY I AZM, CLR I Campylobacter jejuni Breakpoints 11 +genus_species is Campylobacter jejuni ERY R AZM, CLR R Campylobacter jejuni Breakpoints 11 +genus_species is Campylobacter jejuni TCY S DOX S Campylobacter jejuni Breakpoints 11 +genus_species is Campylobacter jejuni TCY I DOX I Campylobacter jejuni Breakpoints 11 +genus_species is Campylobacter jejuni TCY R DOX R Campylobacter jejuni Breakpoints 11 +genus_species is Aerococcus sanguinicola NOR S fluoroquinolones S Aerococcus sanguinicola Breakpoints 11 +genus_species is Aerococcus sanguinicola NOR I fluoroquinolones I Aerococcus sanguinicola Breakpoints 11 +genus_species is Aerococcus sanguinicola NOR R fluoroquinolones R Aerococcus sanguinicola Breakpoints 11 +genus_species is Aerococcus sanguinicola CIP S LVX S Aerococcus sanguinicola Breakpoints 11 +genus_species is Aerococcus sanguinicola CIP I LVX I Aerococcus sanguinicola Breakpoints 11 +genus_species is Aerococcus sanguinicola CIP R LVX R Aerococcus urinae Breakpoints 11 +genus_species is Aerococcus urinae NOR S fluoroquinolones S Aerococcus urinae Breakpoints 11 +genus_species is Aerococcus urinae NOR I fluoroquinolones I Aerococcus urinae Breakpoints 11 +genus_species is Aerococcus urinae NOR R fluoroquinolones R Aerococcus urinae Breakpoints 11 +genus_species is Aerococcus urinae CIP S LVX S Aerococcus urinae Breakpoints 11 +genus_species is Aerococcus urinae CIP I LVX I Aerococcus urinae Breakpoints 11 +genus_species is Aerococcus urinae CIP R LVX R Aerococcus urinae Breakpoints 11 +genus_species is Kingella kingae PEN S AMP, AMX S Kingella kingae Breakpoints 11 +genus_species is Kingella kingae PEN I AMP, AMX I Kingella kingae Breakpoints 11 +genus_species is Kingella kingae PEN R AMP, AMX R Kingella kingae Breakpoints 11 +genus_species is Kingella kingae ERY S AZM, CLR S Kingella kingae Breakpoints 11 +genus_species is Kingella kingae ERY I AZM, CLR I Kingella kingae Breakpoints 11 +genus_species is Kingella kingae ERY R AZM, CLR R Kingella kingae Breakpoints 11 +genus_species is Kingella kingae TCY S DOX S Kingella kingae Breakpoints 11 +genus_species is Kingella kingae TCY I DOX I Kingella kingae Breakpoints 11 +genus_species is Kingella kingae TCY R DOX R Kingella kingae Breakpoints 11 +genus_species is Burkholderia pseudomallei TCY S DOX S Burkholderia pseudomallei Breakpoints 11 +genus_species is Burkholderia pseudomallei TCY I DOX I Burkholderia pseudomallei Breakpoints 11 +genus_species is Burkholderia pseudomallei TCY R DOX R Burkholderia pseudomallei Breakpoints 11 +genus is Bacillus NOR S fluoroquinolones S Bacillus Breakpoints 11 added in 11 +genus is Bacillus NOR I fluoroquinolones I Bacillus Breakpoints 11 added in 11 +genus is Bacillus NOR R fluoroquinolones R Bacillus Breakpoints 11 added in 11 order is Enterobacterales PEN, glycopeptides, FUS, macrolides, LIN, streptogramins, RIF, DAP, LNZ R Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae) Expert Rules 3.1 fullname like ^Citrobacter (koseri|amalonaticus|sedlakii|farmeri|rodentium) aminopenicillins, TIC R Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae) Expert Rules 3.1 fullname like ^Citrobacter (freundii|braakii|murliniae|werkmanii|youngae) aminopenicillins, AMC, CZO, FOX R Table 01: Intrinsic resistance in Enterobacterales (at the time: Enterobacteriaceae) Expert Rules 3.1 diff --git a/data-raw/read_EUCAST.R b/data-raw/read_EUCAST.R index d75e9eb4..b1864914 100644 --- a/data-raw/read_EUCAST.R +++ b/data-raw/read_EUCAST.R @@ -25,6 +25,7 @@ library(openxlsx) library(dplyr) +library(tidyr) library(cleaner) library(AMR) @@ -32,9 +33,18 @@ library(AMR) read_EUCAST <- function(sheet, file, guideline_name) { - message("Getting sheet ", sheet) + message("\nGetting sheet: ", sheet) sheet.bak <- sheet + uncertainties <- NULL + add_uncertainties <- function(old, new) { + if (is.null(old)) { + new + } else { + bind_rows(old, new) + } + } + raw_data <- read.xlsx(xlsxFile = file, sheet = sheet, colNames = FALSE, @@ -42,6 +52,12 @@ read_EUCAST <- function(sheet, file, guideline_name) { skipEmptyCols = FALSE, fillMergedCells = TRUE, na.strings = c("", "-", "NA", "IE", "IP")) + probable_rows <- suppressWarnings(raw_data %>% mutate_all(as.double) %>% summarise_all(~sum(!is.na(.))) %>% unlist() %>% max()) + if (probable_rows == 0) { + message("NO ROWS FOUND") + message("------------------------") + return(NULL) + } # in the info header in the Excel file, EUCAST mentions which genera are targeted if (sheet %like% "anaerob.*Gram.*posi") { @@ -69,7 +85,8 @@ read_EUCAST <- function(sheet, file, guideline_name) { } else if (sheet %like% "PK.*PD") { sheet <- "UNKNOWN" } - mo_sheet <- paste0(as.mo(unlist(strsplit(sheet, "_"))), collapse = "|") + mo_sheet <- paste0(suppressMessages(as.mo(unlist(strsplit(sheet, "_")))), collapse = "|") + if (!is.null(mo_uncertainties())) uncertainties <- add_uncertainties(uncertainties, mo_uncertainties()) set_columns_names <- function(x, cols) { colnames(x) <- cols[1:length(colnames(x))] @@ -80,7 +97,8 @@ read_EUCAST <- function(sheet, file, guideline_name) { for (i in seq_len(length(x))) { y <- trimws(unlist(strsplit(x[i], "(,|and)"))) y <- trimws(gsub("[(].*[)]", "", y)) - y <- suppressWarnings(as.mo(y, allow_uncertain = FALSE)) + y <- suppressWarnings(suppressMessages(as.mo(y, allow_uncertain = FALSE))) + if (!is.null(mo_uncertainties())) uncertainties <<- add_uncertainties(uncertainties, mo_uncertainties()) y <- y[!is.na(y) & y != "UNKNOWN"] x[i] <- paste(y, collapse = "|") } @@ -153,7 +171,8 @@ read_EUCAST <- function(sheet, file, guideline_name) { mutate(drug = gsub(" ?[(, ].*$", "", drug), drug = gsub("[1-9]+$", "", drug), ab = as.ab(drug)) %>% - select(ab, mo, everything(), -drug) + select(ab, mo, everything(), -drug) %>% + as.data.frame(stringsAsFactors = FALSE) # new row for every different MO mentioned for (i in 1:nrow(cleaned)) { @@ -162,7 +181,7 @@ read_EUCAST <- function(sheet, file, guideline_name) { mo_vect <- unlist(strsplit(mo, "|", fixed = TRUE)) cleaned[i, "mo"] <- mo_vect[1] for (j in seq_len(length(mo_vect))) { - cleaned <- bind_rows(cleaned, cleaned[i ,]) + cleaned <- bind_rows(cleaned, cleaned[i , , drop = FALSE]) cleaned[nrow(cleaned), "mo"] <- mo_vect[j] } } @@ -190,41 +209,26 @@ read_EUCAST <- function(sheet, file, guideline_name) { ref_tbl = sheet.bak, disk_dose = ifelse(!is.na(disk_dose), paste0(disk_dose, "ug"), NA_character_), breakpoint_S, - breakpoint_R) + breakpoint_R) %>% + as.data.frame(stringsAsFactors = FALSE) + if (!is.null(uncertainties)) { + print(uncertainties %>% distinct(input, mo, .keep_all = TRUE)) + } + + message("Estimated: ", probable_rows, ", gained: ", cleaned %>% count(ab) %>% nrow()) + message("------------------------") cleaned } -sheets_to_analyse <- c("Enterobacterales", - "Pseudomonas", - "S.maltophilia", - "Acinetobacter", - "Staphylococcus", - "Enterococcus", - "Streptococcus A,B,C,G", - "S.pneumoniae", - "Viridans group streptococci", - "H.influenzae", - "M.catarrhalis", - "N.gonorrhoeae", - "N.meningitidis", - "Anaerobes, Grampositive", - "C.difficile", - "Anaerobes, Gramnegative", - "H.pylori", - "L.monocytogenes", - "P.multocida", - "C.jejuni_C.coli", - "Corynebacterium", - "A.sanguinicola_A.urinae", - "K.kingae", - "Aeromonas", - "B.pseudomallei", - "M.tuberculosis", - "PK PD breakpoints") -file <- "data-raw/v_10.0_Breakpoint_Tables.xlsx" -guideline_name <- "EUCAST 2020" +# Actual import ----------------------------------------------------------- + +file <- "data-raw/v_11.0_Breakpoint_Tables.xlsx" +sheets <- readxl::excel_sheets(file) +guideline_name <- "EUCAST 2021" + +sheets_to_analyse <- sheets[!sheets %in% c("Content", "Changes", "Notes", "Guidance", "Dosages", "Technical uncertainty", "Topical agents")] # takes the longest time: new_EUCAST <- read_EUCAST(sheet = sheets_to_analyse[1], diff --git a/data-raw/reproduction_of_antibiotics.R b/data-raw/reproduction_of_antibiotics.R index 98129888..d0673bec 100644 --- a/data-raw/reproduction_of_antibiotics.R +++ b/data-raw/reproduction_of_antibiotics.R @@ -606,6 +606,20 @@ antibiotics <- antibiotics %>% TRUE ~ group)) antibiotics[which(antibiotics$ab %in% c("CYC", "LNZ", "THA", "TZD")), "group"] <- "Oxazolidinones" +# add pretomanid +antibiotics <- antibiotics %>% + mutate(ab = as.character(ab)) %>% + bind_rows(antibiotics %>% + mutate(ab = as.character(ab)) %>% + filter(ab == "SMF") %>% + mutate(ab = "PMD", + atc = "J04AK08", + cid = 456199, + name = "Pretomanid", + abbreviations = list(""), + oral_ddd = NA_real_)) + + # update DDDs from WHOCC website ddd_oral <- double(length = nrow(antibiotics)) ddd_iv <- double(length = nrow(antibiotics)) diff --git a/data-raw/reproduction_of_eucast_dosage.R b/data-raw/reproduction_of_eucast_dosage.R new file mode 100644 index 00000000..62a8eeab --- /dev/null +++ b/data-raw/reproduction_of_eucast_dosage.R @@ -0,0 +1,130 @@ +# ==================================================================== # +# TITLE # +# Antimicrobial Resistance (AMR) Analysis for R # +# # +# SOURCE # +# https://github.com/msberends/AMR # +# # +# LICENCE # +# (c) 2018-2021 Berends MS, Luz CF et al. # +# Developed at the University of Groningen, the Netherlands, in # +# collaboration with non-profit organisations Certe Medical # +# Diagnostics & Advice, and University Medical Center Groningen. # +# # +# This R package is free software; you can freely use and distribute # +# it for both personal and commercial purposes under the terms of the # +# GNU General Public License version 2.0 (GNU GPL-2), as published by # +# the Free Software Foundation. # +# We created this package for both routine data analysis and academic # +# research and it was publicly released in the hope that it will be # +# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. # +# # +# Visit our website for the full manual and a complete tutorial about # +# how to conduct AMR analysis: https://msberends.github.io/AMR/ # +# ==================================================================== # + +library(dplyr) +library(readxl) +library(cleaner) + +# URL: +# https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/Dosages_v_11.0_Breakpoint_Tables.pdf +# download the PDF file, open in Acrobat Pro and export as Excel workbook +breakpoints_version <- 11 + +dosage_source <- read_excel("data-raw/Dosages_v_11.0_Breakpoint_Tables.xlsx", skip = 5, na = "None") %>% + format_names(snake_case = TRUE, penicillins = "drug") %>% + filter(!tolower(standard_dosage) %in% c("standard dosage_source", "under review")) %>% + filter(!is.na(standard_dosage)) %>% + # keep only one drug in the table + arrange(desc(drug)) %>% + mutate(drug = gsub("(.*) ([(]|iv|oral).*", "\\1", drug)) %>% + #distinct(drug, .keep_all = TRUE) %>% + arrange(drug) %>% + mutate(ab = as.ab(drug), + ab_name = ab_name(ab, language = NULL)) + +get_dosage_lst <- function(col_data) { + standard <- col_data %>% + # remove new lines + gsub(" ?(\n|\t)+ ?", " ", .) %>% + # keep only the first suggestion, replace all after 'or' and more informative texts + gsub("(.*?) (or|with|loading|depending|over|by) .*", "\\1", .) %>% + # remove (1 MU) + gsub(" [(][0-9] [A-Z]+[)]", "", .) %>% + # remove parentheses + gsub("[)(]", "", .) %>% + # remove drug names + gsub(" [a-z]{5,99}( |$)", " ", .) %>% + gsub(" [a-z]{5,99}( |$)", " ", .) %>% + gsub(" (acid|dose)", "", .)# %>% + # keep lowest value only (25-30 mg -> 25 mg) + # gsub("[-].*? ", " ", .) + + dosage_lst <- lapply(strsplit(standard, " x "), + function(x) { + dose <- x[1] + if (dose %like% "under") { + dose <- NA_character_ + } + admin <- x[2] + + list( + dose = trimws(dose), + dose_times = gsub("^([0-9.]+).*", "\\1", admin), + administration = clean_character(admin), + notes = "", + original_txt = "" + ) + }) + for (i in seq_len(length(col_data))) { + dosage_lst[[i]]$original_txt <- gsub("\n", " ", col_data[i]) + if (col_data[i] %like% " (or|with|loading|depending|over) ") { + dosage_lst[[i]]$notes <- gsub("\n", " ", gsub(".* ((or|with|loading|depending|over) .*)", "\\1", col_data[i])) + } + } + dosage_lst +} + +standard <- get_dosage_lst(dosage_source$standard_dosage) +high <- get_dosage_lst(dosage_source$high_dosage) +uti <- get_dosage_lst(dosage_source$uncomplicated_uti) +dosage <- bind_rows( + data.frame( + ab = dosage_source$ab, + name = dosage_source$ab_name, + type = "standard_dosage", + dose = sapply(standard, function(x) x$dose), + dose_times = sapply(standard, function(x) x$dose_times), + administration = sapply(standard, function(x) x$administration), + notes = sapply(standard, function(x) x$notes), + original_txt = sapply(standard, function(x) x$original_txt), + stringsAsFactors = FALSE + ), + data.frame( + ab = dosage_source$ab, + name = dosage_source$ab_name, + type = "high_dosage", + dose = sapply(high, function(x) x$dose), + dose_times = sapply(high, function(x) x$dose_times), + administration = sapply(high, function(x) x$administration), + notes = sapply(high, function(x) x$notes), + original_txt = sapply(high, function(x) x$original_txt), + stringsAsFactors = FALSE + ), + data.frame( + ab = dosage_source$ab, + name = dosage_source$ab_name, + type = "uncomplicated_uti", + dose = sapply(uti, function(x) x$dose), + dose_times = sapply(uti, function(x) x$dose_times), + administration = sapply(uti, function(x) x$administration), + notes = sapply(uti, function(x) x$notes), + original_txt = sapply(uti, function(x) x$original_txt), + stringsAsFactors = FALSE + )) %>% + mutate(eucast_version = breakpoints_version) %>% + arrange(name, administration, type) %>% + filter(!is.na(dose), dose != ".") + +usethis::use_data(dosage, internal = FALSE, overwrite = TRUE, version = 2) diff --git a/data-raw/reproduction_of_rsi_translation.R b/data-raw/reproduction_of_rsi_translation.R index 52b8f677..f79b8f6d 100644 --- a/data-raw/reproduction_of_rsi_translation.R +++ b/data-raw/reproduction_of_rsi_translation.R @@ -77,6 +77,7 @@ clsi_general <- read_tsv("data-raw/DRGLST.txt") %>% # add new EUCAST with read_EUCAST.R # 2020-04-14 did that now for 2019 and 2020 + rsi_trans <- rsi_trans %>% filter(guideline != "EUCAST 2019") %>% bind_rows(new_EUCAST) %>% @@ -88,6 +89,17 @@ rsi_trans <- rsi_trans %>% ab = as.ab(ab)) %>% arrange(desc(guideline), ab, mo, method) +# 2021-01-12 did that now for 2021 +rsi_trans <- rsi_trans %>% + mutate(mo = as.character(mo)) %>% + bind_rows(new_EUCAST) %>% + mutate(uti = site %like% "(UTI|urinary)") %>% + as.data.frame(stringsAsFactors = FALSE) %>% + # force classes again + mutate(mo = as.mo(mo), + ab = as.ab(ab)) %>% + arrange(desc(guideline), ab, mo, method) + # save to package rsi_translation <- rsi_trans usethis::use_data(rsi_translation, overwrite = TRUE) diff --git a/data-raw/rsi.md5 b/data-raw/rsi.md5 index 58469c85..e5ebc6ad 100644 --- a/data-raw/rsi.md5 +++ b/data-raw/rsi.md5 @@ -1 +1 @@ -c589396a6728f7c72def07b4dfb35e28 +f816b536ddd71d00e1adcdaba97d0329 diff --git a/data-raw/rsi_translation.dta b/data-raw/rsi_translation.dta index b5a7172d..302ff862 100644 Binary files a/data-raw/rsi_translation.dta and b/data-raw/rsi_translation.dta differ diff --git a/data-raw/rsi_translation.rds b/data-raw/rsi_translation.rds index 74c77ce6..aef430d0 100644 Binary files a/data-raw/rsi_translation.rds and b/data-raw/rsi_translation.rds differ diff --git a/data-raw/rsi_translation.sas b/data-raw/rsi_translation.sas index 71f9ec47..77669b7d 100644 Binary files a/data-raw/rsi_translation.sas and b/data-raw/rsi_translation.sas differ diff --git a/data-raw/rsi_translation.sav b/data-raw/rsi_translation.sav index ac8c161d..1784e586 100644 Binary files a/data-raw/rsi_translation.sav and b/data-raw/rsi_translation.sav differ diff --git a/data-raw/rsi_translation.txt b/data-raw/rsi_translation.txt index 09779e84..ce30cf1a 100644 --- a/data-raw/rsi_translation.txt +++ b/data-raw/rsi_translation.txt @@ -1,4 +1,1840 @@ "guideline" "method" "site" "mo" "ab" "ref_tbl" "disk_dose" "breakpoint_S" "breakpoint_R" "uti" +"EUCAST 2021" "DISK" "Enterobacterales" "Amoxicillin/clavulanic acid" "Enterobacterales" "20-10ug" 19 19 FALSE +"EUCAST 2021" "DISK" "UTI" "Enterobacterales" "Amoxicillin/clavulanic acid" "Enterobacterales" "20-10ug" 16 16 TRUE +"EUCAST 2021" "MIC" "Enterobacterales" "Amoxicillin/clavulanic acid" "Enterobacterales" 8 8 FALSE +"EUCAST 2021" "MIC" "UTI" "Enterobacterales" "Amoxicillin/clavulanic acid" "Enterobacterales" 32 32 TRUE +"EUCAST 2021" "MIC" "Actinomyces" "Amoxicillin/clavulanic acid" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Bacteroides" "Amoxicillin/clavulanic acid" "Anaerobes, Gramnegative" 4 8 FALSE +"EUCAST 2021" "MIC" "Bifidobacterium" "Amoxicillin/clavulanic acid" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Bilophila" "Amoxicillin/clavulanic acid" "Anaerobes, Gramnegative" 4 8 FALSE +"EUCAST 2021" "DISK" "Burkholderia pseudomallei" "Amoxicillin/clavulanic acid" "B.pseudomallei" "20-10ug" 50 22 FALSE +"EUCAST 2021" "MIC" "Burkholderia pseudomallei" "Amoxicillin/clavulanic acid" "B.pseudomallei" 0.001 8 FALSE +"EUCAST 2021" "MIC" "Clostridioides" "Amoxicillin/clavulanic acid" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Cutibacterium" "Amoxicillin/clavulanic acid" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Clostridium" "Amoxicillin/clavulanic acid" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Eubacterium" "Amoxicillin/clavulanic acid" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Eggerthella" "Amoxicillin/clavulanic acid" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Enterococcus" "Amoxicillin/clavulanic acid" "Enterococcus" 4 8 FALSE +"EUCAST 2021" "MIC" "Fusobacterium" "Amoxicillin/clavulanic acid" "Anaerobes, Gramnegative" 4 8 FALSE +"EUCAST 2021" "DISK" "iv" "Haemophilus influenzae" "Amoxicillin/clavulanic acid" "H.influenzae" "2-1ug" 15 15 FALSE +"EUCAST 2021" "DISK" "oral" "Haemophilus influenzae" "Amoxicillin/clavulanic acid" "H.influenzae" "2-1ug" 50 15 FALSE +"EUCAST 2021" "MIC" "iv" "Haemophilus influenzae" "Amoxicillin/clavulanic acid" "H.influenzae" 2 2 FALSE +"EUCAST 2021" "MIC" "oral" "Haemophilus influenzae" "Amoxicillin/clavulanic acid" "H.influenzae" 0.001 2 FALSE +"EUCAST 2021" "MIC" "Lactobacillus" "Amoxicillin/clavulanic acid" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Mobiluncus" "Amoxicillin/clavulanic acid" "Anaerobes, Gramnegative" 4 8 FALSE +"EUCAST 2021" "DISK" "Moraxella catarrhalis" "Amoxicillin/clavulanic acid" "M.catarrhalis" "2-1ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Moraxella catarrhalis" "Amoxicillin/clavulanic acid" "M.catarrhalis" 1 1 FALSE +"EUCAST 2021" "MIC" "Parabacteroides" "Amoxicillin/clavulanic acid" "Anaerobes, Gramnegative" 4 8 FALSE +"EUCAST 2021" "MIC" "Porphyromonas" "Amoxicillin/clavulanic acid" "Anaerobes, Gramnegative" 4 8 FALSE +"EUCAST 2021" "MIC" "Propionibacterium" "Amoxicillin/clavulanic acid" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Prevotella" "Amoxicillin/clavulanic acid" "Anaerobes, Gramnegative" 4 8 FALSE +"EUCAST 2021" "DISK" "Pasteurella multocida" "Amoxicillin/clavulanic acid" "P.multocida" "2-1ug" 15 15 FALSE +"EUCAST 2021" "MIC" "Pasteurella multocida" "Amoxicillin/clavulanic acid" "P.multocida" 1 1 FALSE +"EUCAST 2021" "MIC" "Staphylococcus saccharolyticus" "Amoxicillin/clavulanic acid" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "oral" "Streptococcus pneumoniae" "Amoxicillin/clavulanic acid" "S.pneumoniae" 0.5 1 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Amoxicillin/clavulanic acid" "PK PD breakpoints" 2 8 FALSE +"EUCAST 2021" "DISK" "Systemic" "Enterobacterales" "Amikacin" "Enterobacterales" "30ug" 18 18 FALSE +"EUCAST 2021" "DISK" "UTI" "Enterobacterales" "Amikacin" "Enterobacterales" "30ug" 18 18 TRUE +"EUCAST 2021" "MIC" "Systemic" "Enterobacterales" "Amikacin" "Enterobacterales" 8 8 FALSE +"EUCAST 2021" "MIC" "UTI" "Enterobacterales" "Amikacin" "Enterobacterales" 8 8 TRUE +"EUCAST 2021" "DISK" "Systemic" "Acinetobacter" "Amikacin" "Acinetobacter" "30ug" 19 19 FALSE +"EUCAST 2021" "DISK" "UTI" "Acinetobacter" "Amikacin" "Acinetobacter" "30ug" 19 19 TRUE +"EUCAST 2021" "MIC" "Systemic" "Acinetobacter" "Amikacin" "Acinetobacter" 8 8 FALSE +"EUCAST 2021" "MIC" "UTI" "Acinetobacter" "Amikacin" "Acinetobacter" 8 8 TRUE +"EUCAST 2021" "DISK" "Systemic" "Pseudomonas" "Amikacin" "Pseudomonas" "30ug" 15 15 FALSE +"EUCAST 2021" "DISK" "UTI" "Pseudomonas" "Amikacin" "Pseudomonas" "30ug" 15 15 TRUE +"EUCAST 2021" "MIC" "Systemic" "Pseudomonas" "Amikacin" "Pseudomonas" 16 16 FALSE +"EUCAST 2021" "MIC" "UTI" "Pseudomonas" "Amikacin" "Pseudomonas" 1 1 TRUE +"EUCAST 2021" "DISK" "Staphylococcus" "Amikacin" "Staphylococcus" "30ug" 22 22 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Amikacin" "Staphylococcus" 8 8 FALSE +"EUCAST 2021" "DISK" "Staphylococcus aureus" "Amikacin" "Staphylococcus" "30ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Staphylococcus aureus" "Amikacin" "Staphylococcus" 8 8 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Amikacin" "PK PD breakpoints" 1 1 FALSE +"EUCAST 2021" "DISK" "Enterobacterales" "Ampicillin" "Enterobacterales" "10ug" 14 14 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Ampicillin" "Enterobacterales" 8 8 FALSE +"EUCAST 2021" "DISK" "Aerococcus sanguinicola" "Ampicillin" "A.sanguinicola_A.urinae" "2ug" 26 26 FALSE +"EUCAST 2021" "MIC" "Aerococcus sanguinicola" "Ampicillin" "A.sanguinicola_A.urinae" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Aerococcus urinae" "Ampicillin" "A.sanguinicola_A.urinae" "2ug" 26 26 FALSE +"EUCAST 2021" "MIC" "Aerococcus urinae" "Ampicillin" "A.sanguinicola_A.urinae" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Actinomyces" "Ampicillin" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Bacteroides" "Ampicillin" "Anaerobes, Gramnegative" 0.5 2 FALSE +"EUCAST 2021" "MIC" "Bifidobacterium" "Ampicillin" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Bilophila" "Ampicillin" "Anaerobes, Gramnegative" 0.5 2 FALSE +"EUCAST 2021" "MIC" "Clostridioides" "Ampicillin" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Cutibacterium" "Ampicillin" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Clostridium" "Ampicillin" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Eubacterium" "Ampicillin" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Eggerthella" "Ampicillin" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "DISK" "Enterococcus" "Ampicillin" "Enterococcus" "2ug" 10 8 FALSE +"EUCAST 2021" "MIC" "Enterococcus" "Ampicillin" "Enterococcus" 4 8 FALSE +"EUCAST 2021" "MIC" "Fusobacterium" "Ampicillin" "Anaerobes, Gramnegative" 0.5 2 FALSE +"EUCAST 2021" "DISK" "Haemophilus influenzae" "Ampicillin" "H.influenzae" "2ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Haemophilus influenzae" "Ampicillin" "H.influenzae" 1 1 FALSE +"EUCAST 2021" "MIC" "Kingella kingae" "Ampicillin" "K.kingae" 0.06 0.06 FALSE +"EUCAST 2021" "MIC" "Lactobacillus" "Ampicillin" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "DISK" "iv" "Listeria monocytogenes" "Ampicillin" "L.monocytogenes" "2ug" 16 16 FALSE +"EUCAST 2021" "MIC" "iv" "Listeria monocytogenes" "Ampicillin" "L.monocytogenes" 1 1 FALSE +"EUCAST 2021" "MIC" "Mobiluncus" "Ampicillin" "Anaerobes, Gramnegative" 0.5 2 FALSE +"EUCAST 2021" "MIC" "Neisseria meningitidis" "Ampicillin" "N.meningitidis" 0.125 1 FALSE +"EUCAST 2021" "MIC" "Parabacteroides" "Ampicillin" "Anaerobes, Gramnegative" 0.5 2 FALSE +"EUCAST 2021" "MIC" "Porphyromonas" "Ampicillin" "Anaerobes, Gramnegative" 0.5 2 FALSE +"EUCAST 2021" "MIC" "Propionibacterium" "Ampicillin" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Prevotella" "Ampicillin" "Anaerobes, Gramnegative" 0.5 2 FALSE +"EUCAST 2021" "MIC" "Pasteurella multocida" "Ampicillin" "P.multocida" 1 1 FALSE +"EUCAST 2021" "MIC" "Staphylococcus saccharolyticus" "Ampicillin" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "DISK" "Streptococcus pneumoniae" "Ampicillin" "S.pneumoniae" "2ug" 22 16 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Ampicillin" "S.pneumoniae" 0.5 2 FALSE +"EUCAST 2021" "DISK" "Viridans Group Streptococcus (VGS)" "Ampicillin" "Viridans group streptococci" "2ug" 21 15 FALSE +"EUCAST 2021" "MIC" "Viridans Group Streptococcus (VGS)" "Ampicillin" "Viridans group streptococci" 0.5 2 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Ampicillin" "PK PD breakpoints" 2 8 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Amoxicillin" "Enterobacterales" 8 8 FALSE +"EUCAST 2021" "MIC" "Actinomyces" "Amoxicillin" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Bacteroides" "Amoxicillin" "Anaerobes, Gramnegative" 0.5 2 FALSE +"EUCAST 2021" "MIC" "Bifidobacterium" "Amoxicillin" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Bilophila" "Amoxicillin" "Anaerobes, Gramnegative" 0.5 2 FALSE +"EUCAST 2021" "MIC" "Clostridioides" "Amoxicillin" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Cutibacterium" "Amoxicillin" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Clostridium" "Amoxicillin" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Eubacterium" "Amoxicillin" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Eggerthella" "Amoxicillin" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Enterococcus" "Amoxicillin" "Enterococcus" 4 8 FALSE +"EUCAST 2021" "MIC" "Fusobacterium" "Amoxicillin" "Anaerobes, Gramnegative" 0.5 2 FALSE +"EUCAST 2021" "MIC" "oral" "Helicobacter pylori" "Amoxicillin" "H.pylori" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "iv" "Haemophilus influenzae" "Amoxicillin" "H.influenzae" 2 2 FALSE +"EUCAST 2021" "MIC" "oral" "Haemophilus influenzae" "Amoxicillin" "H.influenzae" 0.001 2 FALSE +"EUCAST 2021" "MIC" "Kingella kingae" "Amoxicillin" "K.kingae" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Lactobacillus" "Amoxicillin" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Mobiluncus" "Amoxicillin" "Anaerobes, Gramnegative" 0.5 2 FALSE +"EUCAST 2021" "MIC" "Neisseria meningitidis" "Amoxicillin" "N.meningitidis" 0.125 1 FALSE +"EUCAST 2021" "MIC" "Parabacteroides" "Amoxicillin" "Anaerobes, Gramnegative" 0.5 2 FALSE +"EUCAST 2021" "MIC" "Porphyromonas" "Amoxicillin" "Anaerobes, Gramnegative" 0.5 2 FALSE +"EUCAST 2021" "MIC" "Propionibacterium" "Amoxicillin" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Prevotella" "Amoxicillin" "Anaerobes, Gramnegative" 0.5 2 FALSE +"EUCAST 2021" "MIC" "Pasteurella multocida" "Amoxicillin" "P.multocida" 1 1 FALSE +"EUCAST 2021" "MIC" "Staphylococcus saccharolyticus" "Amoxicillin" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "iv" "Streptococcus pneumoniae" "Amoxicillin" "S.pneumoniae" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "oral" "Streptococcus pneumoniae" "Amoxicillin" "S.pneumoniae" 0.5 1 FALSE +"EUCAST 2021" "MIC" "Viridans Group Streptococcus (VGS)" "Amoxicillin" "Viridans group streptococci" 0.5 2 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Amoxicillin" "PK PD breakpoints" 2 8 FALSE +"EUCAST 2021" "DISK" "Enterobacterales" "Aztreonam" "Enterobacterales" "30ug" 26 21 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Aztreonam" "Enterobacterales" 1 4 FALSE +"EUCAST 2021" "DISK" "Aeromonas" "Aztreonam" "Aeromonas" "30ug" 29 26 FALSE +"EUCAST 2021" "MIC" "Aeromonas" "Aztreonam" "Aeromonas" 1 4 FALSE +"EUCAST 2021" "DISK" "Pseudomonas" "Aztreonam" "Pseudomonas" "30ug" 50 18 FALSE +"EUCAST 2021" "MIC" "Pseudomonas" "Aztreonam" "Pseudomonas" 0.001 1 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Aztreonam" "PK PD breakpoints" 4 8 FALSE +"EUCAST 2021" "MIC" "Kingella kingae" "Azithromycin" "K.kingae" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Moraxella catarrhalis" "Azithromycin" "M.catarrhalis" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Azithromycin" "Staphylococcus" 1 2 FALSE +"EUCAST 2021" "MIC" "Streptococcus agalactiae" "Azithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Azithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus whileyi" "Azithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae" "Azithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae equisimilis" "Azithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi" "Azithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi ruminatorum" "Azithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi zooepidemicus" "Azithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus group A" "Azithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus group B" "Azithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus group C" "Azithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus group D" "Azithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus group F" "Azithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus group G" "Azithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus group H" "Azithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus group K" "Azithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Azithromycin" "S.pneumoniae" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus pyogenes" "Azithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius" "Azithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius thermophilus" "Azithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus sanguinis" "Azithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Mycobacterium tuberculosis" "Bedaquiline" "M.tuberculosis" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Enterobacterales" "Ceftobiprole" "Enterobacterales" "5ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Ceftobiprole" "Enterobacterales" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Staphylococcus aureus" "Ceftobiprole" "Staphylococcus" "5ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Staphylococcus aureus" "Ceftobiprole" "Staphylococcus" 2 2 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Ceftobiprole" "S.pneumoniae" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Ceftobiprole" "PK PD breakpoints" 4 4 FALSE +"EUCAST 2021" "DISK" "Enterobacterales" "Ceftazidime" "Enterobacterales" "10ug" 22 19 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Ceftazidime" "Enterobacterales" 1 4 FALSE +"EUCAST 2021" "DISK" "Aeromonas" "Ceftazidime" "Aeromonas" "10ug" 24 21 FALSE +"EUCAST 2021" "MIC" "Aeromonas" "Ceftazidime" "Aeromonas" 1 4 FALSE +"EUCAST 2021" "DISK" "Burkholderia pseudomallei" "Ceftazidime" "B.pseudomallei" "10ug" 50 18 FALSE +"EUCAST 2021" "MIC" "Burkholderia pseudomallei" "Ceftazidime" "B.pseudomallei" 0.001 8 FALSE +"EUCAST 2021" "DISK" "Pseudomonas" "Ceftazidime" "Pseudomonas" "10ug" 50 17 FALSE +"EUCAST 2021" "MIC" "Pseudomonas" "Ceftazidime" "Pseudomonas" 0.001 8 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Ceftazidime" "PK PD breakpoints" 4 8 FALSE +"EUCAST 2021" "DISK" "Streptococcus pneumoniae" "Cefaclor" "S.pneumoniae" "30ug" 50 28 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Cefaclor" "S.pneumoniae" 0.001 0.5 FALSE +"EUCAST 2021" "DISK" "UTI" "Enterobacterales" "Cefixime" "Enterobacterales" "5ug" 17 17 TRUE +"EUCAST 2021" "MIC" "UTI" "Enterobacterales" "Cefixime" "Enterobacterales" 1 1 TRUE +"EUCAST 2021" "DISK" "Haemophilus influenzae" "Cefixime" "H.influenzae" "5ug" 26 26 FALSE +"EUCAST 2021" "MIC" "Haemophilus influenzae" "Cefixime" "H.influenzae" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Moraxella catarrhalis" "Cefixime" "M.catarrhalis" "5ug" 21 18 FALSE +"EUCAST 2021" "MIC" "Moraxella catarrhalis" "Cefixime" "M.catarrhalis" 0.5 1 FALSE +"EUCAST 2021" "MIC" "Neisseria gonorrhoeae" "Cefixime" "N.gonorrhoeae" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "UTI" "Enterobacterales" "Cefadroxil" "Enterobacterales" "30ug" 12 12 TRUE +"EUCAST 2021" "MIC" "UTI" "Enterobacterales" "Cefadroxil" "Enterobacterales" 1 1 TRUE +"EUCAST 2021" "DISK" "Enterobacterales" "Chloramphenicol" "Enterobacterales" "30ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Chloramphenicol" "Enterobacterales" 8 8 FALSE +"EUCAST 2021" "MIC" "Actinomyces" "Chloramphenicol" "Anaerobes, Grampositive" 8 8 FALSE +"EUCAST 2021" "MIC" "Bacteroides" "Chloramphenicol" "Anaerobes, Gramnegative" 8 8 FALSE +"EUCAST 2021" "MIC" "Bifidobacterium" "Chloramphenicol" "Anaerobes, Grampositive" 8 8 FALSE +"EUCAST 2021" "MIC" "Bilophila" "Chloramphenicol" "Anaerobes, Gramnegative" 8 8 FALSE +"EUCAST 2021" "DISK" "Burkholderia pseudomallei" "Chloramphenicol" "B.pseudomallei" "30ug" 50 22 FALSE +"EUCAST 2021" "MIC" "Burkholderia pseudomallei" "Chloramphenicol" "B.pseudomallei" 0.001 8 FALSE +"EUCAST 2021" "MIC" "Clostridioides" "Chloramphenicol" "Anaerobes, Grampositive" 8 8 FALSE +"EUCAST 2021" "MIC" "Cutibacterium" "Chloramphenicol" "Anaerobes, Grampositive" 8 8 FALSE +"EUCAST 2021" "MIC" "Clostridium" "Chloramphenicol" "Anaerobes, Grampositive" 8 8 FALSE +"EUCAST 2021" "MIC" "Eubacterium" "Chloramphenicol" "Anaerobes, Grampositive" 8 8 FALSE +"EUCAST 2021" "MIC" "Eggerthella" "Chloramphenicol" "Anaerobes, Grampositive" 8 8 FALSE +"EUCAST 2021" "MIC" "Fusobacterium" "Chloramphenicol" "Anaerobes, Gramnegative" 8 8 FALSE +"EUCAST 2021" "DISK" "Haemophilus influenzae" "Chloramphenicol" "H.influenzae" "30ug" 28 28 FALSE +"EUCAST 2021" "MIC" "Haemophilus influenzae" "Chloramphenicol" "H.influenzae" 2 2 FALSE +"EUCAST 2021" "MIC" "Lactobacillus" "Chloramphenicol" "Anaerobes, Grampositive" 8 8 FALSE +"EUCAST 2021" "MIC" "Mobiluncus" "Chloramphenicol" "Anaerobes, Gramnegative" 8 8 FALSE +"EUCAST 2021" "MIC" "Neisseria meningitidis" "Chloramphenicol" "N.meningitidis" 2 2 FALSE +"EUCAST 2021" "MIC" "Parabacteroides" "Chloramphenicol" "Anaerobes, Gramnegative" 8 8 FALSE +"EUCAST 2021" "MIC" "Porphyromonas" "Chloramphenicol" "Anaerobes, Gramnegative" 8 8 FALSE +"EUCAST 2021" "MIC" "Propionibacterium" "Chloramphenicol" "Anaerobes, Grampositive" 8 8 FALSE +"EUCAST 2021" "MIC" "Prevotella" "Chloramphenicol" "Anaerobes, Gramnegative" 8 8 FALSE +"EUCAST 2021" "DISK" "Staphylococcus" "Chloramphenicol" "Staphylococcus" "30ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Chloramphenicol" "Staphylococcus" 8 8 FALSE +"EUCAST 2021" "MIC" "Staphylococcus saccharolyticus" "Chloramphenicol" "Anaerobes, Grampositive" 8 8 FALSE +"EUCAST 2021" "DISK" "Streptococcus agalactiae" "Chloramphenicol" "Streptococcus A,B,C,G" "30ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus agalactiae" "Chloramphenicol" "Streptococcus A,B,C,G" 8 8 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus" "Chloramphenicol" "Streptococcus A,B,C,G" "30ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Chloramphenicol" "Streptococcus A,B,C,G" 8 8 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus whileyi" "Chloramphenicol" "Streptococcus A,B,C,G" "30ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus whileyi" "Chloramphenicol" "Streptococcus A,B,C,G" 8 8 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae" "Chloramphenicol" "Streptococcus A,B,C,G" "30ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae" "Chloramphenicol" "Streptococcus A,B,C,G" 8 8 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae equisimilis" "Chloramphenicol" "Streptococcus A,B,C,G" "30ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae equisimilis" "Chloramphenicol" "Streptococcus A,B,C,G" 8 8 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi" "Chloramphenicol" "Streptococcus A,B,C,G" "30ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi" "Chloramphenicol" "Streptococcus A,B,C,G" 8 8 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi ruminatorum" "Chloramphenicol" "Streptococcus A,B,C,G" "30ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi ruminatorum" "Chloramphenicol" "Streptococcus A,B,C,G" 8 8 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi zooepidemicus" "Chloramphenicol" "Streptococcus A,B,C,G" "30ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi zooepidemicus" "Chloramphenicol" "Streptococcus A,B,C,G" 8 8 FALSE +"EUCAST 2021" "DISK" "Streptococcus group A" "Chloramphenicol" "Streptococcus A,B,C,G" "30ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group A" "Chloramphenicol" "Streptococcus A,B,C,G" 8 8 FALSE +"EUCAST 2021" "DISK" "Streptococcus group B" "Chloramphenicol" "Streptococcus A,B,C,G" "30ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group B" "Chloramphenicol" "Streptococcus A,B,C,G" 8 8 FALSE +"EUCAST 2021" "DISK" "Streptococcus group C" "Chloramphenicol" "Streptococcus A,B,C,G" "30ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group C" "Chloramphenicol" "Streptococcus A,B,C,G" 8 8 FALSE +"EUCAST 2021" "DISK" "Streptococcus group D" "Chloramphenicol" "Streptococcus A,B,C,G" "30ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group D" "Chloramphenicol" "Streptococcus A,B,C,G" 8 8 FALSE +"EUCAST 2021" "DISK" "Streptococcus group F" "Chloramphenicol" "Streptococcus A,B,C,G" "30ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group F" "Chloramphenicol" "Streptococcus A,B,C,G" 8 8 FALSE +"EUCAST 2021" "DISK" "Streptococcus group G" "Chloramphenicol" "Streptococcus A,B,C,G" "30ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group G" "Chloramphenicol" "Streptococcus A,B,C,G" 8 8 FALSE +"EUCAST 2021" "DISK" "Streptococcus group H" "Chloramphenicol" "Streptococcus A,B,C,G" "30ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group H" "Chloramphenicol" "Streptococcus A,B,C,G" 8 8 FALSE +"EUCAST 2021" "DISK" "Streptococcus group K" "Chloramphenicol" "Streptococcus A,B,C,G" "30ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group K" "Chloramphenicol" "Streptococcus A,B,C,G" 8 8 FALSE +"EUCAST 2021" "DISK" "Streptococcus pneumoniae" "Chloramphenicol" "S.pneumoniae" "30ug" 21 21 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Chloramphenicol" "S.pneumoniae" 8 8 FALSE +"EUCAST 2021" "DISK" "Streptococcus pyogenes" "Chloramphenicol" "Streptococcus A,B,C,G" "30ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus pyogenes" "Chloramphenicol" "Streptococcus A,B,C,G" 8 8 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius" "Chloramphenicol" "Streptococcus A,B,C,G" "30ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius" "Chloramphenicol" "Streptococcus A,B,C,G" 8 8 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius thermophilus" "Chloramphenicol" "Streptococcus A,B,C,G" "30ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius thermophilus" "Chloramphenicol" "Streptococcus A,B,C,G" 8 8 FALSE +"EUCAST 2021" "DISK" "Streptococcus sanguinis" "Chloramphenicol" "Streptococcus A,B,C,G" "30ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus sanguinis" "Chloramphenicol" "Streptococcus A,B,C,G" 8 8 FALSE +"EUCAST 2021" "DISK" "Enterobacterales" "Ciprofloxacin" "Enterobacterales" "5ug" 25 22 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Ciprofloxacin" "Enterobacterales" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Acinetobacter" "Ciprofloxacin" "Acinetobacter" "5ug" 50 21 FALSE +"EUCAST 2021" "MIC" "Acinetobacter" "Ciprofloxacin" "Acinetobacter" 0.001 1 FALSE +"EUCAST 2021" "DISK" "UTI" "Aerococcus sanguinicola" "Ciprofloxacin" "A.sanguinicola_A.urinae" "5ug" 21 21 TRUE +"EUCAST 2021" "MIC" "UTI" "Aerococcus sanguinicola" "Ciprofloxacin" "A.sanguinicola_A.urinae" 2 2 TRUE +"EUCAST 2021" "DISK" "UTI" "Aerococcus urinae" "Ciprofloxacin" "A.sanguinicola_A.urinae" "5ug" 21 21 TRUE +"EUCAST 2021" "MIC" "UTI" "Aerococcus urinae" "Ciprofloxacin" "A.sanguinicola_A.urinae" 2 2 TRUE +"EUCAST 2021" "DISK" "Aeromonas" "Ciprofloxacin" "Aeromonas" "5ug" 27 24 FALSE +"EUCAST 2021" "MIC" "Aeromonas" "Ciprofloxacin" "Aeromonas" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Bacillus" "Ciprofloxacin" "Bacillus" "5ug" 50 23 FALSE +"EUCAST 2021" "MIC" "Bacillus" "Ciprofloxacin" "Bacillus" 0.001 0.5 FALSE +"EUCAST 2021" "DISK" "Campylobacter coli" "Ciprofloxacin" "C.jejuni_C.coli" "5ug" 50 26 FALSE +"EUCAST 2021" "MIC" "Campylobacter coli" "Ciprofloxacin" "C.jejuni_C.coli" 0.001 0.5 FALSE +"EUCAST 2021" "DISK" "Campylobacter jejuni" "Ciprofloxacin" "C.jejuni_C.coli" "5ug" 50 26 FALSE +"EUCAST 2021" "MIC" "Campylobacter jejuni" "Ciprofloxacin" "C.jejuni_C.coli" 0.001 0.5 FALSE +"EUCAST 2021" "DISK" "Corynebacterium" "Ciprofloxacin" "Corynebacterium" "5ug" 50 25 FALSE +"EUCAST 2021" "MIC" "Corynebacterium" "Ciprofloxacin" "Corynebacterium" 0.001 1 FALSE +"EUCAST 2021" "DISK" "UTI" "Enterococcus" "Ciprofloxacin" "Enterococcus" "5ug" 15 15 TRUE +"EUCAST 2021" "MIC" "UTI" "Enterococcus" "Ciprofloxacin" "Enterococcus" 4 4 TRUE +"EUCAST 2021" "DISK" "Haemophilus influenzae" "Ciprofloxacin" "H.influenzae" "5ug" 30 30 FALSE +"EUCAST 2021" "MIC" "Haemophilus influenzae" "Ciprofloxacin" "H.influenzae" 0.06 0.06 FALSE +"EUCAST 2021" "DISK" "Kingella kingae" "Ciprofloxacin" "K.kingae" "5ug" 28 28 FALSE +"EUCAST 2021" "MIC" "Kingella kingae" "Ciprofloxacin" "K.kingae" 0.06 0.06 FALSE +"EUCAST 2021" "DISK" "Moraxella catarrhalis" "Ciprofloxacin" "M.catarrhalis" "5ug" 31 31 FALSE +"EUCAST 2021" "MIC" "Moraxella catarrhalis" "Ciprofloxacin" "M.catarrhalis" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Neisseria gonorrhoeae" "Ciprofloxacin" "N.gonorrhoeae" 0.03 0.06 FALSE +"EUCAST 2021" "MIC" "Neisseria meningitidis" "Ciprofloxacin" "N.meningitidis" 0.03 0.03 FALSE +"EUCAST 2021" "DISK" "Pseudomonas" "Ciprofloxacin" "Pseudomonas" "5ug" 50 26 FALSE +"EUCAST 2021" "MIC" "Pseudomonas" "Ciprofloxacin" "Pseudomonas" 0.001 0.5 FALSE +"EUCAST 2021" "DISK" "Pasteurella multocida" "Ciprofloxacin" "P.multocida" "5ug" 27 27 FALSE +"EUCAST 2021" "MIC" "Pasteurella multocida" "Ciprofloxacin" "P.multocida" 0.06 0.06 FALSE +"EUCAST 2021" "MIC" "Salmonella" "Ciprofloxacin" "Enterobacterales" 0.06 0.06 FALSE +"EUCAST 2021" "DISK" "Staphylococcus" "Ciprofloxacin" "Staphylococcus" "5ug" 50 24 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Ciprofloxacin" "Staphylococcus" 0.001 1 FALSE +"EUCAST 2021" "DISK" "Staphylococcus aureus" "Ciprofloxacin" "Staphylococcus" "5ug" 50 21 FALSE +"EUCAST 2021" "MIC" "Staphylococcus aureus" "Ciprofloxacin" "Staphylococcus" 0.001 1 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Ciprofloxacin" "PK PD breakpoints" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Actinomyces" "Clindamycin" "Anaerobes, Grampositive" 4 4 FALSE +"EUCAST 2021" "DISK" "Bacillus" "Clindamycin" "Bacillus" "2ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Bacillus" "Clindamycin" "Bacillus" 1 1 FALSE +"EUCAST 2021" "MIC" "Bacteroides" "Clindamycin" "Anaerobes, Gramnegative" 4 4 FALSE +"EUCAST 2021" "MIC" "Bifidobacterium" "Clindamycin" "Anaerobes, Grampositive" 4 4 FALSE +"EUCAST 2021" "MIC" "Bilophila" "Clindamycin" "Anaerobes, Gramnegative" 4 4 FALSE +"EUCAST 2021" "MIC" "Clostridioides" "Clindamycin" "Anaerobes, Grampositive" 4 4 FALSE +"EUCAST 2021" "DISK" "Corynebacterium" "Clindamycin" "Corynebacterium" "2ug" 20 20 FALSE +"EUCAST 2021" "MIC" "Corynebacterium" "Clindamycin" "Corynebacterium" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Cutibacterium" "Clindamycin" "Anaerobes, Grampositive" 4 4 FALSE +"EUCAST 2021" "MIC" "Clostridium" "Clindamycin" "Anaerobes, Grampositive" 4 4 FALSE +"EUCAST 2021" "MIC" "Eubacterium" "Clindamycin" "Anaerobes, Grampositive" 4 4 FALSE +"EUCAST 2021" "MIC" "Eggerthella" "Clindamycin" "Anaerobes, Grampositive" 4 4 FALSE +"EUCAST 2021" "MIC" "Fusobacterium" "Clindamycin" "Anaerobes, Gramnegative" 4 4 FALSE +"EUCAST 2021" "MIC" "Lactobacillus" "Clindamycin" "Anaerobes, Grampositive" 4 4 FALSE +"EUCAST 2021" "MIC" "Mobiluncus" "Clindamycin" "Anaerobes, Gramnegative" 4 4 FALSE +"EUCAST 2021" "MIC" "Parabacteroides" "Clindamycin" "Anaerobes, Gramnegative" 4 4 FALSE +"EUCAST 2021" "MIC" "Porphyromonas" "Clindamycin" "Anaerobes, Gramnegative" 4 4 FALSE +"EUCAST 2021" "MIC" "Propionibacterium" "Clindamycin" "Anaerobes, Grampositive" 4 4 FALSE +"EUCAST 2021" "MIC" "Prevotella" "Clindamycin" "Anaerobes, Gramnegative" 4 4 FALSE +"EUCAST 2021" "DISK" "Staphylococcus" "Clindamycin" "Staphylococcus" "2ug" 22 19 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Clindamycin" "Staphylococcus" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Staphylococcus saccharolyticus" "Clindamycin" "Anaerobes, Grampositive" 4 4 FALSE +"EUCAST 2021" "DISK" "Streptococcus agalactiae" "Clindamycin" "Streptococcus A,B,C,G" "2ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus agalactiae" "Clindamycin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus" "Clindamycin" "Streptococcus A,B,C,G" "2ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Clindamycin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus whileyi" "Clindamycin" "Streptococcus A,B,C,G" "2ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus whileyi" "Clindamycin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae" "Clindamycin" "Streptococcus A,B,C,G" "2ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae" "Clindamycin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae equisimilis" "Clindamycin" "Streptococcus A,B,C,G" "2ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae equisimilis" "Clindamycin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi" "Clindamycin" "Streptococcus A,B,C,G" "2ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi" "Clindamycin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi ruminatorum" "Clindamycin" "Streptococcus A,B,C,G" "2ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi ruminatorum" "Clindamycin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi zooepidemicus" "Clindamycin" "Streptococcus A,B,C,G" "2ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi zooepidemicus" "Clindamycin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group A" "Clindamycin" "Streptococcus A,B,C,G" "2ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus group A" "Clindamycin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group B" "Clindamycin" "Streptococcus A,B,C,G" "2ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus group B" "Clindamycin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group C" "Clindamycin" "Streptococcus A,B,C,G" "2ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus group C" "Clindamycin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group D" "Clindamycin" "Streptococcus A,B,C,G" "2ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus group D" "Clindamycin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group F" "Clindamycin" "Streptococcus A,B,C,G" "2ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus group F" "Clindamycin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group G" "Clindamycin" "Streptococcus A,B,C,G" "2ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus group G" "Clindamycin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group H" "Clindamycin" "Streptococcus A,B,C,G" "2ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus group H" "Clindamycin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group K" "Clindamycin" "Streptococcus A,B,C,G" "2ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus group K" "Clindamycin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus pneumoniae" "Clindamycin" "S.pneumoniae" "2ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Clindamycin" "S.pneumoniae" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus pyogenes" "Clindamycin" "Streptococcus A,B,C,G" "2ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus pyogenes" "Clindamycin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius" "Clindamycin" "Streptococcus A,B,C,G" "2ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius" "Clindamycin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius thermophilus" "Clindamycin" "Streptococcus A,B,C,G" "2ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius thermophilus" "Clindamycin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus sanguinis" "Clindamycin" "Streptococcus A,B,C,G" "2ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus sanguinis" "Clindamycin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Viridans Group Streptococcus (VGS)" "Clindamycin" "Viridans group streptococci" "2ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Viridans Group Streptococcus (VGS)" "Clindamycin" "Viridans group streptococci" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Helicobacter pylori" "Clarithromycin" "H.pylori" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Kingella kingae" "Clarithromycin" "K.kingae" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Moraxella catarrhalis" "Clarithromycin" "M.catarrhalis" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Clarithromycin" "Staphylococcus" 1 2 FALSE +"EUCAST 2021" "MIC" "Streptococcus agalactiae" "Clarithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Clarithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus whileyi" "Clarithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae" "Clarithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae equisimilis" "Clarithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi" "Clarithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi ruminatorum" "Clarithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi zooepidemicus" "Clarithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus group A" "Clarithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus group B" "Clarithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus group C" "Clarithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus group D" "Clarithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus group F" "Clarithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus group G" "Clarithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus group H" "Clarithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus group K" "Clarithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Clarithromycin" "S.pneumoniae" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus pyogenes" "Clarithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius" "Clarithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius thermophilus" "Clarithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus sanguinis" "Clarithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Colistin" "Enterobacterales" 2 2 FALSE +"EUCAST 2021" "MIC" "Acinetobacter" "Colistin" "Acinetobacter" 2 2 FALSE +"EUCAST 2021" "MIC" "Pseudomonas" "Colistin" "Pseudomonas" 2 2 FALSE +"EUCAST 2021" "DISK" "UTI" "Enterobacterales" "Cefpodoxime" "Enterobacterales" "10ug" 21 21 TRUE +"EUCAST 2021" "MIC" "UTI" "Enterobacterales" "Cefpodoxime" "Enterobacterales" 1 1 TRUE +"EUCAST 2021" "DISK" "Haemophilus influenzae" "Cefpodoxime" "H.influenzae" "10ug" 26 26 FALSE +"EUCAST 2021" "MIC" "Haemophilus influenzae" "Cefpodoxime" "H.influenzae" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Cefpodoxime" "S.pneumoniae" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Enterobacterales" "Ceftaroline" "Enterobacterales" "5ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Ceftaroline" "Enterobacterales" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Haemophilus influenzae" "Ceftaroline" "H.influenzae" 0.03 0.03 FALSE +"EUCAST 2021" "DISK" "Staphylococcus aureus" "Ceftaroline" "Staphylococcus" "5ug" 20 17 FALSE +"EUCAST 2021" "MIC" "Staphylococcus aureus" "Ceftaroline" "Staphylococcus" 1 2 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Ceftaroline" "S.pneumoniae" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Ceftaroline" "PK PD breakpoints" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Enterobacterales" "Ceftriaxone" "Enterobacterales" "30ug" 25 22 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Ceftriaxone" "Enterobacterales" 1 2 FALSE +"EUCAST 2021" "DISK" "Haemophilus influenzae" "Ceftriaxone" "H.influenzae" "30ug" 32 32 FALSE +"EUCAST 2021" "MIC" "Haemophilus influenzae" "Ceftriaxone" "H.influenzae" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Kingella kingae" "Ceftriaxone" "K.kingae" "30ug" 30 30 FALSE +"EUCAST 2021" "MIC" "Kingella kingae" "Ceftriaxone" "K.kingae" 0.06 0.06 FALSE +"EUCAST 2021" "DISK" "Moraxella catarrhalis" "Ceftriaxone" "M.catarrhalis" "30ug" 24 21 FALSE +"EUCAST 2021" "MIC" "Moraxella catarrhalis" "Ceftriaxone" "M.catarrhalis" 1 2 FALSE +"EUCAST 2021" "MIC" "Neisseria gonorrhoeae" "Ceftriaxone" "N.gonorrhoeae" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Neisseria meningitidis" "Ceftriaxone" "N.meningitidis" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Ceftriaxone" "S.pneumoniae" 0.5 2 FALSE +"EUCAST 2021" "DISK" "Viridans Group Streptococcus (VGS)" "Ceftriaxone" "Viridans group streptococci" "30ug" 27 27 FALSE +"EUCAST 2021" "MIC" "Viridans Group Streptococcus (VGS)" "Ceftriaxone" "Viridans group streptococci" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Ceftriaxone" "PK PD breakpoints" 1 2 FALSE +"EUCAST 2021" "DISK" "UTI" "Enterobacterales" "Ceftibuten" "Enterobacterales" "30ug" 23 23 TRUE +"EUCAST 2021" "MIC" "UTI" "Enterobacterales" "Ceftibuten" "Enterobacterales" 1 1 TRUE +"EUCAST 2021" "DISK" "Haemophilus influenzae" "Ceftibuten" "H.influenzae" "30ug" 25 25 FALSE +"EUCAST 2021" "MIC" "Haemophilus influenzae" "Ceftibuten" "H.influenzae" 1 1 FALSE +"EUCAST 2021" "DISK" "Enterobacterales" "Cefotaxime" "Enterobacterales" "5ug" 20 17 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Cefotaxime" "Enterobacterales" 1 2 FALSE +"EUCAST 2021" "DISK" "Haemophilus influenzae" "Cefotaxime" "H.influenzae" "5ug" 27 27 FALSE +"EUCAST 2021" "MIC" "Haemophilus influenzae" "Cefotaxime" "H.influenzae" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Kingella kingae" "Cefotaxime" "K.kingae" "5ug" 27 27 FALSE +"EUCAST 2021" "MIC" "Kingella kingae" "Cefotaxime" "K.kingae" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Moraxella catarrhalis" "Cefotaxime" "M.catarrhalis" "5ug" 20 17 FALSE +"EUCAST 2021" "MIC" "Moraxella catarrhalis" "Cefotaxime" "M.catarrhalis" 1 2 FALSE +"EUCAST 2021" "MIC" "Neisseria gonorrhoeae" "Cefotaxime" "N.gonorrhoeae" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Neisseria meningitidis" "Cefotaxime" "N.meningitidis" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Pasteurella multocida" "Cefotaxime" "P.multocida" "5ug" 26 26 FALSE +"EUCAST 2021" "MIC" "Pasteurella multocida" "Cefotaxime" "P.multocida" 0.03 0.03 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Cefotaxime" "S.pneumoniae" 0.5 2 FALSE +"EUCAST 2021" "DISK" "Viridans Group Streptococcus (VGS)" "Cefotaxime" "Viridans group streptococci" "5ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Viridans Group Streptococcus (VGS)" "Cefotaxime" "Viridans group streptococci" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Cefotaxime" "PK PD breakpoints" 1 2 FALSE +"EUCAST 2021" "DISK" "iv" "Escherichia coli" "Cefuroxime" "Enterobacterales" "30ug" 50 19 FALSE +"EUCAST 2021" "DISK" "UTI" "Escherichia coli" "Cefuroxime" "Enterobacterales" "30ug" 19 19 TRUE +"EUCAST 2021" "MIC" "iv" "Escherichia coli" "Cefuroxime" "Enterobacterales" 0.001 8 FALSE +"EUCAST 2021" "MIC" "UTI" "Escherichia coli" "Cefuroxime" "Enterobacterales" 8 8 TRUE +"EUCAST 2021" "DISK" "iv" "Haemophilus influenzae" "Cefuroxime" "H.influenzae" "30ug" 27 25 FALSE +"EUCAST 2021" "DISK" "oral" "Haemophilus influenzae" "Cefuroxime" "H.influenzae" "30ug" 50 27 FALSE +"EUCAST 2021" "MIC" "iv" "Haemophilus influenzae" "Cefuroxime" "H.influenzae" 1 2 FALSE +"EUCAST 2021" "MIC" "oral" "Haemophilus influenzae" "Cefuroxime" "H.influenzae" 0.001 1 FALSE +"EUCAST 2021" "DISK" "iv" "Kingella kingae" "Cefuroxime" "K.kingae" "30ug" 29 29 FALSE +"EUCAST 2021" "MIC" "iv" "Kingella kingae" "Cefuroxime" "K.kingae" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "iv" "Klebsiella" "Cefuroxime" "Enterobacterales" "30ug" 50 19 FALSE +"EUCAST 2021" "DISK" "UTI" "Klebsiella" "Cefuroxime" "Enterobacterales" "30ug" 19 19 TRUE +"EUCAST 2021" "MIC" "iv" "Klebsiella" "Cefuroxime" "Enterobacterales" 0.001 8 FALSE +"EUCAST 2021" "MIC" "UTI" "Klebsiella" "Cefuroxime" "Enterobacterales" 8 8 TRUE +"EUCAST 2021" "DISK" "iv" "Moraxella catarrhalis" "Cefuroxime" "M.catarrhalis" "30ug" 21 18 FALSE +"EUCAST 2021" "DISK" "oral" "Moraxella catarrhalis" "Cefuroxime" "M.catarrhalis" "30ug" 50 21 FALSE +"EUCAST 2021" "MIC" "iv" "Moraxella catarrhalis" "Cefuroxime" "M.catarrhalis" 4 8 FALSE +"EUCAST 2021" "MIC" "oral" "Moraxella catarrhalis" "Cefuroxime" "M.catarrhalis" 0.001 4 FALSE +"EUCAST 2021" "DISK" "iv" "Proteus mirabilis" "Cefuroxime" "Enterobacterales" "30ug" 50 19 FALSE +"EUCAST 2021" "DISK" "UTI" "Proteus mirabilis" "Cefuroxime" "Enterobacterales" "30ug" 19 19 TRUE +"EUCAST 2021" "MIC" "iv" "Proteus mirabilis" "Cefuroxime" "Enterobacterales" 0.001 8 FALSE +"EUCAST 2021" "MIC" "UTI" "Proteus mirabilis" "Cefuroxime" "Enterobacterales" 8 8 TRUE +"EUCAST 2021" "DISK" "iv" "Raoultella" "Cefuroxime" "Enterobacterales" "30ug" 50 19 FALSE +"EUCAST 2021" "DISK" "UTI" "Raoultella" "Cefuroxime" "Enterobacterales" "30ug" 19 19 TRUE +"EUCAST 2021" "MIC" "iv" "Raoultella" "Cefuroxime" "Enterobacterales" 0.001 8 FALSE +"EUCAST 2021" "MIC" "UTI" "Raoultella" "Cefuroxime" "Enterobacterales" 8 8 TRUE +"EUCAST 2021" "MIC" "iv" "Streptococcus pneumoniae" "Cefuroxime" "S.pneumoniae" 0.5 1 FALSE +"EUCAST 2021" "MIC" "oral" "Streptococcus pneumoniae" "Cefuroxime" "S.pneumoniae" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "iv" "Viridans Group Streptococcus (VGS)" "Cefuroxime" "Viridans group streptococci" "30ug" 26 26 FALSE +"EUCAST 2021" "MIC" "iv" "Viridans Group Streptococcus (VGS)" "Cefuroxime" "Viridans group streptococci" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "iv" "(unknown name)" "Cefuroxime" "PK PD breakpoints" 4 8 FALSE +"EUCAST 2021" "DISK" "Enterobacterales" "Ceftazidime/avibactam" "Enterobacterales" "10-4ug" 13 13 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Ceftazidime/avibactam" "Enterobacterales" 8 8 FALSE +"EUCAST 2021" "DISK" "Pseudomonas aeruginosa" "Ceftazidime/avibactam" "Pseudomonas" "10-4ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Pseudomonas aeruginosa" "Ceftazidime/avibactam" "Pseudomonas" 8 8 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Ceftazidime/avibactam" "PK PD breakpoints" 8 8 FALSE +"EUCAST 2021" "DISK" "UTI" "Escherichia coli" "Cefazolin" "Enterobacterales" "30ug" 50 20 TRUE +"EUCAST 2021" "MIC" "UTI" "Escherichia coli" "Cefazolin" "Enterobacterales" 0.001 4 TRUE +"EUCAST 2021" "DISK" "UTI" "Klebsiella" "Cefazolin" "Enterobacterales" "30ug" 50 20 TRUE +"EUCAST 2021" "MIC" "UTI" "Klebsiella" "Cefazolin" "Enterobacterales" 0.001 4 TRUE +"EUCAST 2021" "MIC" "(unknown name)" "Cefazolin" "PK PD breakpoints" 1 2 FALSE +"EUCAST 2021" "DISK" "Enterobacterales" "Ceftolozane/tazobactam" "Enterobacterales" "30-10ug" 22 22 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Ceftolozane/tazobactam" "Enterobacterales" 2 2 FALSE +"EUCAST 2021" "DISK" "Haemophilus influenzae" "Ceftolozane/tazobactam" "H.influenzae" "30-10ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Haemophilus influenzae" "Ceftolozane/tazobactam" "H.influenzae" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Pseudomonas aeruginosa" "Ceftolozane/tazobactam" "Pseudomonas" "30-10ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Pseudomonas aeruginosa" "Ceftolozane/tazobactam" "Pseudomonas" 4 4 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Ceftolozane/tazobactam" "PK PD breakpoints" 44.5 44.5 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Dalbavancin" "Staphylococcus" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Streptococcus agalactiae" "Dalbavancin" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Dalbavancin" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Dalbavancin" "Viridans group streptococci" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus whileyi" "Dalbavancin" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae" "Dalbavancin" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae equisimilis" "Dalbavancin" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi" "Dalbavancin" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi ruminatorum" "Dalbavancin" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi zooepidemicus" "Dalbavancin" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Streptococcus group A" "Dalbavancin" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Streptococcus group B" "Dalbavancin" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Streptococcus group C" "Dalbavancin" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Streptococcus group D" "Dalbavancin" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Streptococcus group F" "Dalbavancin" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Streptococcus group G" "Dalbavancin" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Streptococcus group H" "Dalbavancin" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Streptococcus group K" "Dalbavancin" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Streptococcus pyogenes" "Dalbavancin" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius" "Dalbavancin" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius thermophilus" "Dalbavancin" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Streptococcus sanguinis" "Dalbavancin" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Dalbavancin" "PK PD breakpoints" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Daptomycin" "Staphylococcus" 1 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus agalactiae" "Daptomycin" "Streptococcus A,B,C,G" 1 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Daptomycin" "Streptococcus A,B,C,G" 1 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus whileyi" "Daptomycin" "Streptococcus A,B,C,G" 1 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae" "Daptomycin" "Streptococcus A,B,C,G" 1 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae equisimilis" "Daptomycin" "Streptococcus A,B,C,G" 1 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi" "Daptomycin" "Streptococcus A,B,C,G" 1 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi ruminatorum" "Daptomycin" "Streptococcus A,B,C,G" 1 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi zooepidemicus" "Daptomycin" "Streptococcus A,B,C,G" 1 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus group A" "Daptomycin" "Streptococcus A,B,C,G" 1 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus group B" "Daptomycin" "Streptococcus A,B,C,G" 1 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus group C" "Daptomycin" "Streptococcus A,B,C,G" 1 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus group D" "Daptomycin" "Streptococcus A,B,C,G" 1 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus group F" "Daptomycin" "Streptococcus A,B,C,G" 1 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus group G" "Daptomycin" "Streptococcus A,B,C,G" 1 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus group H" "Daptomycin" "Streptococcus A,B,C,G" 1 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus group K" "Daptomycin" "Streptococcus A,B,C,G" 1 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus pyogenes" "Daptomycin" "Streptococcus A,B,C,G" 1 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius" "Daptomycin" "Streptococcus A,B,C,G" 1 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius thermophilus" "Daptomycin" "Streptococcus A,B,C,G" 1 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus sanguinis" "Daptomycin" "Streptococcus A,B,C,G" 1 1 FALSE +"EUCAST 2021" "MIC" "Escherichia coli" "Delafloxacin" "Enterobacterales" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Staphylococcus aureus" "Delafloxacin" "Staphylococcus" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Streptococcus agalactiae" "Delafloxacin" "Streptococcus A,B,C,G" 0.03 0.03 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Delafloxacin" "Streptococcus A,B,C,G" 0.03 0.03 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Delafloxacin" "Viridans group streptococci" 0.03 0.03 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus whileyi" "Delafloxacin" "Streptococcus A,B,C,G" 0.03 0.03 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae" "Delafloxacin" "Streptococcus A,B,C,G" 0.03 0.03 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae equisimilis" "Delafloxacin" "Streptococcus A,B,C,G" 0.03 0.03 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi" "Delafloxacin" "Streptococcus A,B,C,G" 0.03 0.03 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi ruminatorum" "Delafloxacin" "Streptococcus A,B,C,G" 0.03 0.03 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi zooepidemicus" "Delafloxacin" "Streptococcus A,B,C,G" 0.03 0.03 FALSE +"EUCAST 2021" "MIC" "Streptococcus group A" "Delafloxacin" "Streptococcus A,B,C,G" 0.03 0.03 FALSE +"EUCAST 2021" "MIC" "Streptococcus group B" "Delafloxacin" "Streptococcus A,B,C,G" 0.03 0.03 FALSE +"EUCAST 2021" "MIC" "Streptococcus group C" "Delafloxacin" "Streptococcus A,B,C,G" 0.03 0.03 FALSE +"EUCAST 2021" "MIC" "Streptococcus group D" "Delafloxacin" "Streptococcus A,B,C,G" 0.03 0.03 FALSE +"EUCAST 2021" "MIC" "Streptococcus group F" "Delafloxacin" "Streptococcus A,B,C,G" 0.03 0.03 FALSE +"EUCAST 2021" "MIC" "Streptococcus group G" "Delafloxacin" "Streptococcus A,B,C,G" 0.03 0.03 FALSE +"EUCAST 2021" "MIC" "Streptococcus group H" "Delafloxacin" "Streptococcus A,B,C,G" 0.03 0.03 FALSE +"EUCAST 2021" "MIC" "Streptococcus group K" "Delafloxacin" "Streptococcus A,B,C,G" 0.03 0.03 FALSE +"EUCAST 2021" "MIC" "Streptococcus pyogenes" "Delafloxacin" "Streptococcus A,B,C,G" 0.03 0.03 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius" "Delafloxacin" "Streptococcus A,B,C,G" 0.03 0.03 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius thermophilus" "Delafloxacin" "Streptococcus A,B,C,G" 0.03 0.03 FALSE +"EUCAST 2021" "MIC" "Streptococcus sanguinis" "Delafloxacin" "Streptococcus A,B,C,G" 0.03 0.03 FALSE +"EUCAST 2021" "MIC" "Mycobacterium tuberculosis" "Delamanid" "M.tuberculosis" 0.06 0.06 FALSE +"EUCAST 2021" "DISK" "Enterobacterales" "Doripenem" "Enterobacterales" "10ug" 24 21 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Doripenem" "Enterobacterales" 1 2 FALSE +"EUCAST 2021" "DISK" "Acinetobacter" "Doripenem" "Acinetobacter" "10ug" 50 22 FALSE +"EUCAST 2021" "MIC" "Acinetobacter" "Doripenem" "Acinetobacter" 0.001 2 FALSE +"EUCAST 2021" "MIC" "Actinomyces" "Doripenem" "Anaerobes, Grampositive" 1 1 FALSE +"EUCAST 2021" "MIC" "Bacteroides" "Doripenem" "Anaerobes, Gramnegative" 1 1 FALSE +"EUCAST 2021" "MIC" "Bifidobacterium" "Doripenem" "Anaerobes, Grampositive" 1 1 FALSE +"EUCAST 2021" "MIC" "Bilophila" "Doripenem" "Anaerobes, Gramnegative" 1 1 FALSE +"EUCAST 2021" "MIC" "Clostridioides" "Doripenem" "Anaerobes, Grampositive" 1 1 FALSE +"EUCAST 2021" "MIC" "Cutibacterium" "Doripenem" "Anaerobes, Grampositive" 1 1 FALSE +"EUCAST 2021" "MIC" "Clostridium" "Doripenem" "Anaerobes, Grampositive" 1 1 FALSE +"EUCAST 2021" "MIC" "Eubacterium" "Doripenem" "Anaerobes, Grampositive" 1 1 FALSE +"EUCAST 2021" "MIC" "Eggerthella" "Doripenem" "Anaerobes, Grampositive" 1 1 FALSE +"EUCAST 2021" "MIC" "Fusobacterium" "Doripenem" "Anaerobes, Gramnegative" 1 1 FALSE +"EUCAST 2021" "DISK" "Haemophilus influenzae" "Doripenem" "H.influenzae" "10ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Haemophilus influenzae" "Doripenem" "H.influenzae" 1 1 FALSE +"EUCAST 2021" "MIC" "Lactobacillus" "Doripenem" "Anaerobes, Grampositive" 1 1 FALSE +"EUCAST 2021" "MIC" "Mobiluncus" "Doripenem" "Anaerobes, Gramnegative" 1 1 FALSE +"EUCAST 2021" "DISK" "Moraxella catarrhalis" "Doripenem" "M.catarrhalis" "10ug" 30 30 FALSE +"EUCAST 2021" "MIC" "Moraxella catarrhalis" "Doripenem" "M.catarrhalis" 1 1 FALSE +"EUCAST 2021" "MIC" "Parabacteroides" "Doripenem" "Anaerobes, Gramnegative" 1 1 FALSE +"EUCAST 2021" "MIC" "Porphyromonas" "Doripenem" "Anaerobes, Gramnegative" 1 1 FALSE +"EUCAST 2021" "MIC" "Propionibacterium" "Doripenem" "Anaerobes, Grampositive" 1 1 FALSE +"EUCAST 2021" "MIC" "Prevotella" "Doripenem" "Anaerobes, Gramnegative" 1 1 FALSE +"EUCAST 2021" "DISK" "Pseudomonas" "Doripenem" "Pseudomonas" "10ug" 50 22 FALSE +"EUCAST 2021" "MIC" "Pseudomonas" "Doripenem" "Pseudomonas" 0.001 2 FALSE +"EUCAST 2021" "MIC" "Staphylococcus saccharolyticus" "Doripenem" "Anaerobes, Grampositive" 1 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Doripenem" "S.pneumoniae" 1 1 FALSE +"EUCAST 2021" "MIC" "Viridans Group Streptococcus (VGS)" "Doripenem" "Viridans group streptococci" 1 1 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Doripenem" "PK PD breakpoints" 1 2 FALSE +"EUCAST 2021" "MIC" "Burkholderia pseudomallei" "Doxycycline" "B.pseudomallei" 0.001 2 FALSE +"EUCAST 2021" "MIC" "Haemophilus influenzae" "Doxycycline" "H.influenzae" 1 2 FALSE +"EUCAST 2021" "MIC" "Kingella kingae" "Doxycycline" "K.kingae" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Moraxella catarrhalis" "Doxycycline" "M.catarrhalis" 1 2 FALSE +"EUCAST 2021" "MIC" "Pasteurella multocida" "Doxycycline" "P.multocida" 1 1 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Doxycycline" "Staphylococcus" 1 2 FALSE +"EUCAST 2021" "MIC" "Streptococcus agalactiae" "Doxycycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Doxycycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus whileyi" "Doxycycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae" "Doxycycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae equisimilis" "Doxycycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi" "Doxycycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi ruminatorum" "Doxycycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi zooepidemicus" "Doxycycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "MIC" "Streptococcus group A" "Doxycycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "MIC" "Streptococcus group B" "Doxycycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "MIC" "Streptococcus group C" "Doxycycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "MIC" "Streptococcus group D" "Doxycycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "MIC" "Streptococcus group F" "Doxycycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "MIC" "Streptococcus group G" "Doxycycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "MIC" "Streptococcus group H" "Doxycycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "MIC" "Streptococcus group K" "Doxycycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Doxycycline" "S.pneumoniae" 1 2 FALSE +"EUCAST 2021" "MIC" "Streptococcus pyogenes" "Doxycycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius" "Doxycycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius thermophilus" "Doxycycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "MIC" "Streptococcus sanguinis" "Doxycycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Enterococcus faecium" "Eravacycline" "Enterococcus" "20ug" 24 24 FALSE +"EUCAST 2021" "MIC" "Enterococcus faecium" "Eravacycline" "Enterococcus" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Enterococcus faecalis" "Eravacycline" "Enterococcus" "20ug" 22 22 FALSE +"EUCAST 2021" "MIC" "Enterococcus faecalis" "Eravacycline" "Enterococcus" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Escherichia coli" "Eravacycline" "Enterobacterales" "20ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Escherichia coli" "Eravacycline" "Enterobacterales" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Staphylococcus aureus" "Eravacycline" "Staphylococcus" "20ug" 20 20 FALSE +"EUCAST 2021" "MIC" "Staphylococcus aureus" "Eravacycline" "Staphylococcus" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Viridans Group Streptococcus (VGS)" "Eravacycline" "Viridans group streptococci" "20ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Viridans Group Streptococcus (VGS)" "Eravacycline" "Viridans group streptococci" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Bacillus" "Erythromycin" "Bacillus" "15ug" 24 24 FALSE +"EUCAST 2021" "MIC" "Bacillus" "Erythromycin" "Bacillus" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Campylobacter coli" "Erythromycin" "C.jejuni_C.coli" "15ug" 24 24 FALSE +"EUCAST 2021" "MIC" "Campylobacter coli" "Erythromycin" "C.jejuni_C.coli" 8 8 FALSE +"EUCAST 2021" "DISK" "Campylobacter jejuni" "Erythromycin" "C.jejuni_C.coli" "15ug" 20 20 FALSE +"EUCAST 2021" "MIC" "Campylobacter jejuni" "Erythromycin" "C.jejuni_C.coli" 4 4 FALSE +"EUCAST 2021" "DISK" "Kingella kingae" "Erythromycin" "K.kingae" "15ug" 20 20 FALSE +"EUCAST 2021" "MIC" "Kingella kingae" "Erythromycin" "K.kingae" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Listeria monocytogenes" "Erythromycin" "L.monocytogenes" "15ug" 25 25 FALSE +"EUCAST 2021" "MIC" "Listeria monocytogenes" "Erythromycin" "L.monocytogenes" 1 1 FALSE +"EUCAST 2021" "DISK" "Moraxella catarrhalis" "Erythromycin" "M.catarrhalis" "15ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Moraxella catarrhalis" "Erythromycin" "M.catarrhalis" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Staphylococcus" "Erythromycin" "Staphylococcus" "15ug" 21 18 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Erythromycin" "Staphylococcus" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus agalactiae" "Erythromycin" "Streptococcus A,B,C,G" "15ug" 21 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus agalactiae" "Erythromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus" "Erythromycin" "Streptococcus A,B,C,G" "15ug" 21 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Erythromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus whileyi" "Erythromycin" "Streptococcus A,B,C,G" "15ug" 21 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus whileyi" "Erythromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae" "Erythromycin" "Streptococcus A,B,C,G" "15ug" 21 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae" "Erythromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae equisimilis" "Erythromycin" "Streptococcus A,B,C,G" "15ug" 21 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae equisimilis" "Erythromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi" "Erythromycin" "Streptococcus A,B,C,G" "15ug" 21 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi" "Erythromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi ruminatorum" "Erythromycin" "Streptococcus A,B,C,G" "15ug" 21 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi ruminatorum" "Erythromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi zooepidemicus" "Erythromycin" "Streptococcus A,B,C,G" "15ug" 21 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi zooepidemicus" "Erythromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group A" "Erythromycin" "Streptococcus A,B,C,G" "15ug" 21 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus group A" "Erythromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group B" "Erythromycin" "Streptococcus A,B,C,G" "15ug" 21 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus group B" "Erythromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group C" "Erythromycin" "Streptococcus A,B,C,G" "15ug" 21 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus group C" "Erythromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group D" "Erythromycin" "Streptococcus A,B,C,G" "15ug" 21 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus group D" "Erythromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group F" "Erythromycin" "Streptococcus A,B,C,G" "15ug" 21 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus group F" "Erythromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group G" "Erythromycin" "Streptococcus A,B,C,G" "15ug" 21 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus group G" "Erythromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group H" "Erythromycin" "Streptococcus A,B,C,G" "15ug" 21 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus group H" "Erythromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group K" "Erythromycin" "Streptococcus A,B,C,G" "15ug" 21 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus group K" "Erythromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus pneumoniae" "Erythromycin" "S.pneumoniae" "15ug" 22 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Erythromycin" "S.pneumoniae" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus pyogenes" "Erythromycin" "Streptococcus A,B,C,G" "15ug" 21 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus pyogenes" "Erythromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius" "Erythromycin" "Streptococcus A,B,C,G" "15ug" 21 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius" "Erythromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius thermophilus" "Erythromycin" "Streptococcus A,B,C,G" "15ug" 21 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius thermophilus" "Erythromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus sanguinis" "Erythromycin" "Streptococcus A,B,C,G" "15ug" 21 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus sanguinis" "Erythromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Enterobacterales" "Ertapenem" "Enterobacterales" "10ug" 25 25 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Ertapenem" "Enterobacterales" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Actinomyces" "Ertapenem" "Anaerobes, Grampositive" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Bacteroides" "Ertapenem" "Anaerobes, Gramnegative" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Bifidobacterium" "Ertapenem" "Anaerobes, Grampositive" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Bilophila" "Ertapenem" "Anaerobes, Gramnegative" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Clostridioides" "Ertapenem" "Anaerobes, Grampositive" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Cutibacterium" "Ertapenem" "Anaerobes, Grampositive" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Clostridium" "Ertapenem" "Anaerobes, Grampositive" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Eubacterium" "Ertapenem" "Anaerobes, Grampositive" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Eggerthella" "Ertapenem" "Anaerobes, Grampositive" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Fusobacterium" "Ertapenem" "Anaerobes, Gramnegative" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Haemophilus influenzae" "Ertapenem" "H.influenzae" "10ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Haemophilus influenzae" "Ertapenem" "H.influenzae" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Lactobacillus" "Ertapenem" "Anaerobes, Grampositive" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Mobiluncus" "Ertapenem" "Anaerobes, Gramnegative" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Moraxella catarrhalis" "Ertapenem" "M.catarrhalis" "10ug" 29 29 FALSE +"EUCAST 2021" "MIC" "Moraxella catarrhalis" "Ertapenem" "M.catarrhalis" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Parabacteroides" "Ertapenem" "Anaerobes, Gramnegative" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Porphyromonas" "Ertapenem" "Anaerobes, Gramnegative" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Propionibacterium" "Ertapenem" "Anaerobes, Grampositive" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Prevotella" "Ertapenem" "Anaerobes, Gramnegative" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Staphylococcus saccharolyticus" "Ertapenem" "Anaerobes, Grampositive" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Ertapenem" "S.pneumoniae" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Viridans Group Streptococcus (VGS)" "Ertapenem" "Viridans group streptococci" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Ertapenem" "PK PD breakpoints" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Enterobacterales" "Cefiderocol" "Enterobacterales" "30ug" 22 22 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Cefiderocol" "Enterobacterales" 2 2 FALSE +"EUCAST 2021" "MIC" "Acinetobacter" "Cefiderocol" "Acinetobacter" 1 1 FALSE +"EUCAST 2021" "DISK" "Pseudomonas aeruginosa" "Cefiderocol" "Pseudomonas" "30ug" 22 22 FALSE +"EUCAST 2021" "MIC" "Pseudomonas aeruginosa" "Cefiderocol" "Pseudomonas" 2 2 FALSE +"EUCAST 2021" "MIC" "Stenotrophomonas maltophilia" "Cefiderocol" "S.maltophilia" 1 1 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Cefiderocol" "PK PD breakpoints" 2 2 FALSE +"EUCAST 2021" "MIC" "Clostridioides difficile" "Fidaxomicin" "C.difficile" 4 4 FALSE +"EUCAST 2021" "DISK" "Enterobacterales" "Cefepime" "Enterobacterales" "30ug" 27 24 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Cefepime" "Enterobacterales" 1 4 FALSE +"EUCAST 2021" "DISK" "Aeromonas" "Cefepime" "Aeromonas" "30ug" 27 24 FALSE +"EUCAST 2021" "MIC" "Aeromonas" "Cefepime" "Aeromonas" 1 4 FALSE +"EUCAST 2021" "DISK" "Haemophilus influenzae" "Cefepime" "H.influenzae" "30ug" 28 28 FALSE +"EUCAST 2021" "MIC" "Haemophilus influenzae" "Cefepime" "H.influenzae" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Moraxella catarrhalis" "Cefepime" "M.catarrhalis" "30ug" 20 20 FALSE +"EUCAST 2021" "MIC" "Moraxella catarrhalis" "Cefepime" "M.catarrhalis" 4 4 FALSE +"EUCAST 2021" "DISK" "Pseudomonas" "Cefepime" "Pseudomonas" "30ug" 50 21 FALSE +"EUCAST 2021" "MIC" "Pseudomonas" "Cefepime" "Pseudomonas" 0.001 8 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Cefepime" "S.pneumoniae" 1 2 FALSE +"EUCAST 2021" "DISK" "Viridans Group Streptococcus (VGS)" "Cefepime" "Viridans group streptococci" "30ug" 25 25 FALSE +"EUCAST 2021" "MIC" "Viridans Group Streptococcus (VGS)" "Cefepime" "Viridans group streptococci" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Cefepime" "PK PD breakpoints" 4 8 FALSE +"EUCAST 2021" "DISK" "iv" "Enterobacterales" "Fosfomycin" "Enterobacterales" "200ug" 21 21 FALSE +"EUCAST 2021" "MIC" "iv" "Enterobacterales" "Fosfomycin" "Enterobacterales" 32 32 FALSE +"EUCAST 2021" "DISK" "UTI" "Escherichia coli" "Fosfomycin" "Enterobacterales" "200ug" 24 24 TRUE +"EUCAST 2021" "MIC" "UTI" "Escherichia coli" "Fosfomycin" "Enterobacterales" 8 8 TRUE +"EUCAST 2021" "MIC" "iv" "Staphylococcus" "Fosfomycin" "Staphylococcus" 32 32 FALSE +"EUCAST 2021" "MIC" "oral" "(unknown name)" "Fosfomycin" "PK PD breakpoints" 8 8 FALSE +"EUCAST 2021" "DISK" "Staphylococcus" "Fusidic acid" "Staphylococcus" "10ug" 24 24 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Fusidic acid" "Staphylococcus" 1 1 FALSE +"EUCAST 2021" "DISK" "Systemic" "Enterobacterales" "Gentamicin" "Enterobacterales" "10ug" 17 17 FALSE +"EUCAST 2021" "DISK" "UTI" "Enterobacterales" "Gentamicin" "Enterobacterales" "10ug" 17 17 TRUE +"EUCAST 2021" "MIC" "Systemic" "Enterobacterales" "Gentamicin" "Enterobacterales" 2 2 FALSE +"EUCAST 2021" "MIC" "UTI" "Enterobacterales" "Gentamicin" "Enterobacterales" 2 2 TRUE +"EUCAST 2021" "DISK" "Systemic" "Acinetobacter" "Gentamicin" "Acinetobacter" "10ug" 17 17 FALSE +"EUCAST 2021" "DISK" "UTI" "Acinetobacter" "Gentamicin" "Acinetobacter" "10ug" 17 17 TRUE +"EUCAST 2021" "MIC" "Systemic" "Acinetobacter" "Gentamicin" "Acinetobacter" 4 4 FALSE +"EUCAST 2021" "MIC" "UTI" "Acinetobacter" "Gentamicin" "Acinetobacter" 4 4 TRUE +"EUCAST 2021" "DISK" "Staphylococcus" "Gentamicin" "Staphylococcus" "10ug" 22 22 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Gentamicin" "Staphylococcus" 1 1 FALSE +"EUCAST 2021" "DISK" "Staphylococcus aureus" "Gentamicin" "Staphylococcus" "10ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Staphylococcus aureus" "Gentamicin" "Staphylococcus" 1 1 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Gentamicin" "PK PD breakpoints" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Enterobacterales" "Imipenem/relebactam" "Enterobacterales" "10-25ug" 22 22 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Imipenem/relebactam" "Enterobacterales" 2 2 FALSE +"EUCAST 2021" "DISK" "Acinetobacter" "Imipenem/relebactam" "Acinetobacter" "10-25ug" 24 24 FALSE +"EUCAST 2021" "MIC" "Acinetobacter" "Imipenem/relebactam" "Acinetobacter" 2 2 FALSE +"EUCAST 2021" "MIC" "Actinomyces" "Imipenem/relebactam" "Anaerobes, Grampositive" 2 2 FALSE +"EUCAST 2021" "MIC" "Bacteroides" "Imipenem/relebactam" "Anaerobes, Gramnegative" 2 2 FALSE +"EUCAST 2021" "MIC" "Bifidobacterium" "Imipenem/relebactam" "Anaerobes, Grampositive" 2 2 FALSE +"EUCAST 2021" "MIC" "Bilophila" "Imipenem/relebactam" "Anaerobes, Gramnegative" 2 2 FALSE +"EUCAST 2021" "MIC" "Clostridioides" "Imipenem/relebactam" "Anaerobes, Grampositive" 2 2 FALSE +"EUCAST 2021" "MIC" "Cutibacterium" "Imipenem/relebactam" "Anaerobes, Grampositive" 2 2 FALSE +"EUCAST 2021" "MIC" "Clostridium" "Imipenem/relebactam" "Anaerobes, Grampositive" 2 2 FALSE +"EUCAST 2021" "MIC" "Eubacterium" "Imipenem/relebactam" "Anaerobes, Grampositive" 2 2 FALSE +"EUCAST 2021" "MIC" "Eggerthella" "Imipenem/relebactam" "Anaerobes, Grampositive" 2 2 FALSE +"EUCAST 2021" "MIC" "Fusobacterium" "Imipenem/relebactam" "Anaerobes, Gramnegative" 2 2 FALSE +"EUCAST 2021" "MIC" "Lactobacillus" "Imipenem/relebactam" "Anaerobes, Grampositive" 2 2 FALSE +"EUCAST 2021" "MIC" "Mobiluncus" "Imipenem/relebactam" "Anaerobes, Gramnegative" 2 2 FALSE +"EUCAST 2021" "MIC" "Parabacteroides" "Imipenem/relebactam" "Anaerobes, Gramnegative" 2 2 FALSE +"EUCAST 2021" "MIC" "Porphyromonas" "Imipenem/relebactam" "Anaerobes, Gramnegative" 2 2 FALSE +"EUCAST 2021" "MIC" "Propionibacterium" "Imipenem/relebactam" "Anaerobes, Grampositive" 2 2 FALSE +"EUCAST 2021" "MIC" "Prevotella" "Imipenem/relebactam" "Anaerobes, Gramnegative" 2 2 FALSE +"EUCAST 2021" "DISK" "Pseudomonas aeruginosa" "Imipenem/relebactam" "Pseudomonas" "10-25ug" 22 22 FALSE +"EUCAST 2021" "MIC" "Pseudomonas aeruginosa" "Imipenem/relebactam" "Pseudomonas" 2 2 FALSE +"EUCAST 2021" "MIC" "Staphylococcus saccharolyticus" "Imipenem/relebactam" "Anaerobes, Grampositive" 2 2 FALSE +"EUCAST 2021" "MIC" "Viridans Group Streptococcus (VGS)" "Imipenem/relebactam" "Viridans group streptococci" 2 2 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Imipenem/relebactam" "PK PD breakpoints" 2 2 FALSE +"EUCAST 2021" "DISK" "Enterobacterales" "Imipenem" "Enterobacterales" "10ug" 22 19 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Imipenem" "Enterobacterales" 2 4 FALSE +"EUCAST 2021" "DISK" "Acinetobacter" "Imipenem" "Acinetobacter" "10ug" 24 21 FALSE +"EUCAST 2021" "MIC" "Acinetobacter" "Imipenem" "Acinetobacter" 2 4 FALSE +"EUCAST 2021" "MIC" "Actinomyces" "Imipenem" "Anaerobes, Grampositive" 2 4 FALSE +"EUCAST 2021" "DISK" "Bacillus" "Imipenem" "Bacillus" "10ug" 30 30 FALSE +"EUCAST 2021" "MIC" "Bacillus" "Imipenem" "Bacillus" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Bacteroides" "Imipenem" "Anaerobes, Gramnegative" 2 4 FALSE +"EUCAST 2021" "MIC" "Bifidobacterium" "Imipenem" "Anaerobes, Grampositive" 2 4 FALSE +"EUCAST 2021" "MIC" "Bilophila" "Imipenem" "Anaerobes, Gramnegative" 2 4 FALSE +"EUCAST 2021" "DISK" "Burkholderia pseudomallei" "Imipenem" "B.pseudomallei" "10ug" 29 29 FALSE +"EUCAST 2021" "MIC" "Burkholderia pseudomallei" "Imipenem" "B.pseudomallei" 2 2 FALSE +"EUCAST 2021" "MIC" "Clostridioides" "Imipenem" "Anaerobes, Grampositive" 2 4 FALSE +"EUCAST 2021" "MIC" "Cutibacterium" "Imipenem" "Anaerobes, Grampositive" 2 4 FALSE +"EUCAST 2021" "MIC" "Clostridium" "Imipenem" "Anaerobes, Grampositive" 2 4 FALSE +"EUCAST 2021" "MIC" "Eubacterium" "Imipenem" "Anaerobes, Grampositive" 2 4 FALSE +"EUCAST 2021" "MIC" "Eggerthella" "Imipenem" "Anaerobes, Grampositive" 2 4 FALSE +"EUCAST 2021" "DISK" "Enterococcus" "Imipenem" "Enterococcus" "10ug" 50 21 FALSE +"EUCAST 2021" "MIC" "Enterococcus" "Imipenem" "Enterococcus" 0.001 4 FALSE +"EUCAST 2021" "MIC" "Fusobacterium" "Imipenem" "Anaerobes, Gramnegative" 2 4 FALSE +"EUCAST 2021" "DISK" "Haemophilus influenzae" "Imipenem" "H.influenzae" "10ug" 20 20 FALSE +"EUCAST 2021" "MIC" "Haemophilus influenzae" "Imipenem" "H.influenzae" 2 2 FALSE +"EUCAST 2021" "MIC" "Lactobacillus" "Imipenem" "Anaerobes, Grampositive" 2 4 FALSE +"EUCAST 2021" "MIC" "Mobiluncus" "Imipenem" "Anaerobes, Gramnegative" 2 4 FALSE +"EUCAST 2021" "DISK" "Moraxella catarrhalis" "Imipenem" "M.catarrhalis" "10ug" 29 29 FALSE +"EUCAST 2021" "MIC" "Moraxella catarrhalis" "Imipenem" "M.catarrhalis" 2 2 FALSE +"EUCAST 2021" "MIC" "Parabacteroides" "Imipenem" "Anaerobes, Gramnegative" 2 4 FALSE +"EUCAST 2021" "MIC" "Porphyromonas" "Imipenem" "Anaerobes, Gramnegative" 2 4 FALSE +"EUCAST 2021" "MIC" "Propionibacterium" "Imipenem" "Anaerobes, Grampositive" 2 4 FALSE +"EUCAST 2021" "MIC" "Prevotella" "Imipenem" "Anaerobes, Gramnegative" 2 4 FALSE +"EUCAST 2021" "DISK" "Pseudomonas" "Imipenem" "Pseudomonas" "10ug" 50 20 FALSE +"EUCAST 2021" "MIC" "Pseudomonas" "Imipenem" "Pseudomonas" 0.001 4 FALSE +"EUCAST 2021" "MIC" "Staphylococcus saccharolyticus" "Imipenem" "Anaerobes, Grampositive" 2 4 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Imipenem" "S.pneumoniae" 2 2 FALSE +"EUCAST 2021" "MIC" "Viridans Group Streptococcus (VGS)" "Imipenem" "Viridans group streptococci" 2 2 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Imipenem" "PK PD breakpoints" 2 4 FALSE +"EUCAST 2021" "DISK" "UTI" "Enterobacterales" "Cephalexin" "Enterobacterales" "30ug" 14 14 TRUE +"EUCAST 2021" "MIC" "UTI" "Enterobacterales" "Cephalexin" "Enterobacterales" 1 1 TRUE +"EUCAST 2021" "DISK" "Staphylococcus aureus" "Lefamulin" "Staphylococcus" "5ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Staphylococcus aureus" "Lefamulin" "Staphylococcus" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Streptococcus pneumoniae" "Lefamulin" "S.pneumoniae" "5ug" 12 12 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Lefamulin" "S.pneumoniae" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Lefamulin" "PK PD breakpoints" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Bacillus" "Linezolid" "Bacillus" "10ug" 22 22 FALSE +"EUCAST 2021" "MIC" "Bacillus" "Linezolid" "Bacillus" 2 2 FALSE +"EUCAST 2021" "DISK" "Corynebacterium" "Linezolid" "Corynebacterium" "10ug" 25 25 FALSE +"EUCAST 2021" "MIC" "Corynebacterium" "Linezolid" "Corynebacterium" 2 2 FALSE +"EUCAST 2021" "DISK" "Enterococcus" "Linezolid" "Enterococcus" "10ug" 20 20 FALSE +"EUCAST 2021" "MIC" "Enterococcus" "Linezolid" "Enterococcus" 4 4 FALSE +"EUCAST 2021" "DISK" "Staphylococcus" "Linezolid" "Staphylococcus" "10ug" 21 21 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Linezolid" "Staphylococcus" 4 4 FALSE +"EUCAST 2021" "DISK" "Streptococcus agalactiae" "Linezolid" "Streptococcus A,B,C,G" "10ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus agalactiae" "Linezolid" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus" "Linezolid" "Streptococcus A,B,C,G" "10ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Linezolid" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus whileyi" "Linezolid" "Streptococcus A,B,C,G" "10ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus whileyi" "Linezolid" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae" "Linezolid" "Streptococcus A,B,C,G" "10ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae" "Linezolid" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae equisimilis" "Linezolid" "Streptococcus A,B,C,G" "10ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae equisimilis" "Linezolid" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi" "Linezolid" "Streptococcus A,B,C,G" "10ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi" "Linezolid" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi ruminatorum" "Linezolid" "Streptococcus A,B,C,G" "10ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi ruminatorum" "Linezolid" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi zooepidemicus" "Linezolid" "Streptococcus A,B,C,G" "10ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi zooepidemicus" "Linezolid" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group A" "Linezolid" "Streptococcus A,B,C,G" "10ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group A" "Linezolid" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group B" "Linezolid" "Streptococcus A,B,C,G" "10ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group B" "Linezolid" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group C" "Linezolid" "Streptococcus A,B,C,G" "10ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group C" "Linezolid" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group D" "Linezolid" "Streptococcus A,B,C,G" "10ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group D" "Linezolid" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group F" "Linezolid" "Streptococcus A,B,C,G" "10ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group F" "Linezolid" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group G" "Linezolid" "Streptococcus A,B,C,G" "10ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group G" "Linezolid" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group H" "Linezolid" "Streptococcus A,B,C,G" "10ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group H" "Linezolid" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group K" "Linezolid" "Streptococcus A,B,C,G" "10ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group K" "Linezolid" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus pneumoniae" "Linezolid" "S.pneumoniae" "10ug" 22 22 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Linezolid" "S.pneumoniae" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus pyogenes" "Linezolid" "Streptococcus A,B,C,G" "10ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus pyogenes" "Linezolid" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius" "Linezolid" "Streptococcus A,B,C,G" "10ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius" "Linezolid" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius thermophilus" "Linezolid" "Streptococcus A,B,C,G" "10ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius thermophilus" "Linezolid" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus sanguinis" "Linezolid" "Streptococcus A,B,C,G" "10ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus sanguinis" "Linezolid" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Linezolid" "PK PD breakpoints" 2 2 FALSE +"EUCAST 2021" "DISK" "Enterobacterales" "Levofloxacin" "Enterobacterales" "5ug" 23 19 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Levofloxacin" "Enterobacterales" 0.5 1 FALSE +"EUCAST 2021" "DISK" "Acinetobacter" "Levofloxacin" "Acinetobacter" "5ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Acinetobacter" "Levofloxacin" "Acinetobacter" 0.5 1 FALSE +"EUCAST 2021" "MIC" "UTI" "Aerococcus sanguinicola" "Levofloxacin" "A.sanguinicola_A.urinae" 2 2 TRUE +"EUCAST 2021" "MIC" "UTI" "Aerococcus urinae" "Levofloxacin" "A.sanguinicola_A.urinae" 2 2 TRUE +"EUCAST 2021" "DISK" "Aeromonas" "Levofloxacin" "Aeromonas" "5ug" 27 24 FALSE +"EUCAST 2021" "MIC" "Aeromonas" "Levofloxacin" "Aeromonas" 0.5 1 FALSE +"EUCAST 2021" "DISK" "Bacillus" "Levofloxacin" "Bacillus" "5ug" 50 23 FALSE +"EUCAST 2021" "MIC" "Bacillus" "Levofloxacin" "Bacillus" 0.001 1 FALSE +"EUCAST 2021" "DISK" "UTI" "Enterococcus" "Levofloxacin" "Enterococcus" "5ug" 15 15 TRUE +"EUCAST 2021" "MIC" "UTI" "Enterococcus" "Levofloxacin" "Enterococcus" 4 4 TRUE +"EUCAST 2021" "MIC" "Helicobacter pylori" "Levofloxacin" "H.pylori" 1 1 FALSE +"EUCAST 2021" "DISK" "Haemophilus influenzae" "Levofloxacin" "H.influenzae" "5ug" 30 30 FALSE +"EUCAST 2021" "MIC" "Haemophilus influenzae" "Levofloxacin" "H.influenzae" 0.06 0.06 FALSE +"EUCAST 2021" "DISK" "Kingella kingae" "Levofloxacin" "K.kingae" "5ug" 28 28 FALSE +"EUCAST 2021" "MIC" "Kingella kingae" "Levofloxacin" "K.kingae" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Moraxella catarrhalis" "Levofloxacin" "M.catarrhalis" "5ug" 29 29 FALSE +"EUCAST 2021" "MIC" "Moraxella catarrhalis" "Levofloxacin" "M.catarrhalis" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Pseudomonas" "Levofloxacin" "Pseudomonas" "5ug" 50 22 FALSE +"EUCAST 2021" "MIC" "Pseudomonas" "Levofloxacin" "Pseudomonas" 0.001 1 FALSE +"EUCAST 2021" "DISK" "Pasteurella multocida" "Levofloxacin" "P.multocida" "5ug" 27 27 FALSE +"EUCAST 2021" "MIC" "Pasteurella multocida" "Levofloxacin" "P.multocida" 0.06 0.06 FALSE +"EUCAST 2021" "DISK" "Staphylococcus" "Levofloxacin" "Staphylococcus" "5ug" 50 24 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Levofloxacin" "Staphylococcus" 0.001 1 FALSE +"EUCAST 2021" "DISK" "Staphylococcus aureus" "Levofloxacin" "Staphylococcus" "5ug" 50 22 FALSE +"EUCAST 2021" "MIC" "Staphylococcus aureus" "Levofloxacin" "Staphylococcus" 0.001 1 FALSE +"EUCAST 2021" "DISK" "Streptococcus agalactiae" "Levofloxacin" "Streptococcus A,B,C,G" "5ug" 50 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus agalactiae" "Levofloxacin" "Streptococcus A,B,C,G" 0.001 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus" "Levofloxacin" "Streptococcus A,B,C,G" "5ug" 50 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Levofloxacin" "Streptococcus A,B,C,G" 0.001 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus whileyi" "Levofloxacin" "Streptococcus A,B,C,G" "5ug" 50 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus whileyi" "Levofloxacin" "Streptococcus A,B,C,G" 0.001 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae" "Levofloxacin" "Streptococcus A,B,C,G" "5ug" 50 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae" "Levofloxacin" "Streptococcus A,B,C,G" 0.001 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae equisimilis" "Levofloxacin" "Streptococcus A,B,C,G" "5ug" 50 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae equisimilis" "Levofloxacin" "Streptococcus A,B,C,G" 0.001 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi" "Levofloxacin" "Streptococcus A,B,C,G" "5ug" 50 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi" "Levofloxacin" "Streptococcus A,B,C,G" 0.001 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi ruminatorum" "Levofloxacin" "Streptococcus A,B,C,G" "5ug" 50 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi ruminatorum" "Levofloxacin" "Streptococcus A,B,C,G" 0.001 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi zooepidemicus" "Levofloxacin" "Streptococcus A,B,C,G" "5ug" 50 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi zooepidemicus" "Levofloxacin" "Streptococcus A,B,C,G" 0.001 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group A" "Levofloxacin" "Streptococcus A,B,C,G" "5ug" 50 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus group A" "Levofloxacin" "Streptococcus A,B,C,G" 0.001 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group B" "Levofloxacin" "Streptococcus A,B,C,G" "5ug" 50 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus group B" "Levofloxacin" "Streptococcus A,B,C,G" 0.001 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group C" "Levofloxacin" "Streptococcus A,B,C,G" "5ug" 50 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus group C" "Levofloxacin" "Streptococcus A,B,C,G" 0.001 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group D" "Levofloxacin" "Streptococcus A,B,C,G" "5ug" 50 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus group D" "Levofloxacin" "Streptococcus A,B,C,G" 0.001 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group F" "Levofloxacin" "Streptococcus A,B,C,G" "5ug" 50 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus group F" "Levofloxacin" "Streptococcus A,B,C,G" 0.001 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group G" "Levofloxacin" "Streptococcus A,B,C,G" "5ug" 50 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus group G" "Levofloxacin" "Streptococcus A,B,C,G" 0.001 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group H" "Levofloxacin" "Streptococcus A,B,C,G" "5ug" 50 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus group H" "Levofloxacin" "Streptococcus A,B,C,G" 0.001 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group K" "Levofloxacin" "Streptococcus A,B,C,G" "5ug" 50 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus group K" "Levofloxacin" "Streptococcus A,B,C,G" 0.001 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus pneumoniae" "Levofloxacin" "S.pneumoniae" "5ug" 50 16 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Levofloxacin" "S.pneumoniae" 0.001 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus pyogenes" "Levofloxacin" "Streptococcus A,B,C,G" "5ug" 50 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus pyogenes" "Levofloxacin" "Streptococcus A,B,C,G" 0.001 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius" "Levofloxacin" "Streptococcus A,B,C,G" "5ug" 50 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius" "Levofloxacin" "Streptococcus A,B,C,G" 0.001 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius thermophilus" "Levofloxacin" "Streptococcus A,B,C,G" "5ug" 50 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius thermophilus" "Levofloxacin" "Streptococcus A,B,C,G" 0.001 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus sanguinis" "Levofloxacin" "Streptococcus A,B,C,G" "5ug" 50 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus sanguinis" "Levofloxacin" "Streptococcus A,B,C,G" 0.001 2 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Levofloxacin" "PK PD breakpoints" 0.5 1 FALSE +"EUCAST 2021" "DISK" "UTI" "Citrobacter" "Mecillinam (Amdinocillin)" "Enterobacterales" "10ug" 15 15 TRUE +"EUCAST 2021" "MIC" "UTI" "Citrobacter" "Mecillinam (Amdinocillin)" "Enterobacterales" 8 8 TRUE +"EUCAST 2021" "DISK" "UTI" "Enterobacter" "Mecillinam (Amdinocillin)" "Enterobacterales" "10ug" 15 15 TRUE +"EUCAST 2021" "MIC" "UTI" "Enterobacter" "Mecillinam (Amdinocillin)" "Enterobacterales" 8 8 TRUE +"EUCAST 2021" "DISK" "UTI" "Escherichia coli" "Mecillinam (Amdinocillin)" "Enterobacterales" "10ug" 15 15 TRUE +"EUCAST 2021" "MIC" "UTI" "Escherichia coli" "Mecillinam (Amdinocillin)" "Enterobacterales" 8 8 TRUE +"EUCAST 2021" "DISK" "UTI" "Klebsiella" "Mecillinam (Amdinocillin)" "Enterobacterales" "10ug" 15 15 TRUE +"EUCAST 2021" "MIC" "UTI" "Klebsiella" "Mecillinam (Amdinocillin)" "Enterobacterales" 8 8 TRUE +"EUCAST 2021" "DISK" "UTI" "Proteus mirabilis" "Mecillinam (Amdinocillin)" "Enterobacterales" "10ug" 15 15 TRUE +"EUCAST 2021" "MIC" "UTI" "Proteus mirabilis" "Mecillinam (Amdinocillin)" "Enterobacterales" 8 8 TRUE +"EUCAST 2021" "DISK" "UTI" "Raoultella" "Mecillinam (Amdinocillin)" "Enterobacterales" "10ug" 15 15 TRUE +"EUCAST 2021" "MIC" "UTI" "Raoultella" "Mecillinam (Amdinocillin)" "Enterobacterales" 8 8 TRUE +"EUCAST 2021" "DISK" "Enterobacterales" "Meropenem" "Enterobacterales" "10ug" 22 16 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Meropenem" "Enterobacterales" 2 8 FALSE +"EUCAST 2021" "DISK" "Achromobacter xylosoxidans" "Meropenem" "A.xylosoxidans" "10ug" 26 20 FALSE +"EUCAST 2021" "MIC" "Achromobacter xylosoxidans" "Meropenem" "A.xylosoxidans" 1 4 FALSE +"EUCAST 2021" "DISK" "Acinetobacter" "Meropenem" "Acinetobacter" "10ug" 21 15 FALSE +"EUCAST 2021" "MIC" "Acinetobacter" "Meropenem" "Acinetobacter" 2 8 FALSE +"EUCAST 2021" "DISK" "Aerococcus sanguinicola" "Meropenem" "A.sanguinicola_A.urinae" "10ug" 31 31 FALSE +"EUCAST 2021" "MIC" "Aerococcus sanguinicola" "Meropenem" "A.sanguinicola_A.urinae" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Aerococcus urinae" "Meropenem" "A.sanguinicola_A.urinae" "10ug" 31 31 FALSE +"EUCAST 2021" "MIC" "Aerococcus urinae" "Meropenem" "A.sanguinicola_A.urinae" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Actinomyces" "Meropenem" "Anaerobes, Grampositive" 2 8 FALSE +"EUCAST 2021" "DISK" "Bacillus" "Meropenem" "Bacillus" "10ug" 25 25 FALSE +"EUCAST 2021" "MIC" "Bacillus" "Meropenem" "Bacillus" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Bacteroides" "Meropenem" "Anaerobes, Gramnegative" 2 8 FALSE +"EUCAST 2021" "MIC" "Bifidobacterium" "Meropenem" "Anaerobes, Grampositive" 2 8 FALSE +"EUCAST 2021" "MIC" "Bilophila" "Meropenem" "Anaerobes, Gramnegative" 2 8 FALSE +"EUCAST 2021" "DISK" "Burkholderia pseudomallei" "Meropenem" "B.pseudomallei" "10ug" 24 24 FALSE +"EUCAST 2021" "MIC" "Burkholderia pseudomallei" "Meropenem" "B.pseudomallei" 2 2 FALSE +"EUCAST 2021" "MIC" "Clostridioides" "Meropenem" "Anaerobes, Grampositive" 2 8 FALSE +"EUCAST 2021" "MIC" "Cutibacterium" "Meropenem" "Anaerobes, Grampositive" 2 8 FALSE +"EUCAST 2021" "MIC" "Clostridium" "Meropenem" "Anaerobes, Grampositive" 2 8 FALSE +"EUCAST 2021" "MIC" "Eubacterium" "Meropenem" "Anaerobes, Grampositive" 2 8 FALSE +"EUCAST 2021" "MIC" "Eggerthella" "Meropenem" "Anaerobes, Grampositive" 2 8 FALSE +"EUCAST 2021" "MIC" "Fusobacterium" "Meropenem" "Anaerobes, Gramnegative" 2 8 FALSE +"EUCAST 2021" "DISK" "Haemophilus influenzae" "Meropenem" "H.influenzae" "10ug" 20 20 FALSE +"EUCAST 2021" "MIC" "Haemophilus influenzae" "Meropenem" "H.influenzae" 2 2 FALSE +"EUCAST 2021" "DISK" "Kingella kingae" "Meropenem" "K.kingae" "10ug" 30 30 FALSE +"EUCAST 2021" "MIC" "Kingella kingae" "Meropenem" "K.kingae" 0.03 0.03 FALSE +"EUCAST 2021" "MIC" "Lactobacillus" "Meropenem" "Anaerobes, Grampositive" 2 8 FALSE +"EUCAST 2021" "DISK" "Listeria monocytogenes" "Meropenem" "L.monocytogenes" "10ug" 26 26 FALSE +"EUCAST 2021" "MIC" "Listeria monocytogenes" "Meropenem" "L.monocytogenes" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Mobiluncus" "Meropenem" "Anaerobes, Gramnegative" 2 8 FALSE +"EUCAST 2021" "DISK" "Moraxella catarrhalis" "Meropenem" "M.catarrhalis" "10ug" 33 33 FALSE +"EUCAST 2021" "MIC" "Moraxella catarrhalis" "Meropenem" "M.catarrhalis" 2 2 FALSE +"EUCAST 2021" "MIC" "Neisseria meningitidis" "Meropenem" "N.meningitidis" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Parabacteroides" "Meropenem" "Anaerobes, Gramnegative" 2 8 FALSE +"EUCAST 2021" "MIC" "Porphyromonas" "Meropenem" "Anaerobes, Gramnegative" 2 8 FALSE +"EUCAST 2021" "MIC" "Propionibacterium" "Meropenem" "Anaerobes, Grampositive" 2 8 FALSE +"EUCAST 2021" "MIC" "Prevotella" "Meropenem" "Anaerobes, Gramnegative" 2 8 FALSE +"EUCAST 2021" "DISK" "Pseudomonas" "Meropenem" "Pseudomonas" "10ug" 24 18 FALSE +"EUCAST 2021" "MIC" "Pseudomonas" "Meropenem" "Pseudomonas" 2 8 FALSE +"EUCAST 2021" "MIC" "Staphylococcus saccharolyticus" "Meropenem" "Anaerobes, Grampositive" 2 8 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Meropenem" "S.pneumoniae" 2 2 FALSE +"EUCAST 2021" "MIC" "Viridans Group Streptococcus (VGS)" "Meropenem" "Viridans group streptococci" 2 2 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Meropenem" "PK PD breakpoints" 2 8 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Meropenem/vaborbactam" "Enterobacterales" 8 8 FALSE +"EUCAST 2021" "MIC" "Pseudomonas aeruginosa" "Meropenem/vaborbactam" "Pseudomonas" 8 8 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Meropenem/vaborbactam" "PK PD breakpoints" 8 8 FALSE +"EUCAST 2021" "DISK" "Enterobacterales" "Moxifloxacin" "Enterobacterales" "5ug" 22 22 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Moxifloxacin" "Enterobacterales" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Corynebacterium" "Moxifloxacin" "Corynebacterium" "5ug" 25 25 FALSE +"EUCAST 2021" "MIC" "Corynebacterium" "Moxifloxacin" "Corynebacterium" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Haemophilus influenzae" "Moxifloxacin" "H.influenzae" "5ug" 28 28 FALSE +"EUCAST 2021" "MIC" "Haemophilus influenzae" "Moxifloxacin" "H.influenzae" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Moraxella catarrhalis" "Moxifloxacin" "M.catarrhalis" "5ug" 26 26 FALSE +"EUCAST 2021" "MIC" "Moraxella catarrhalis" "Moxifloxacin" "M.catarrhalis" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Staphylococcus" "Moxifloxacin" "Staphylococcus" "5ug" 28 28 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Moxifloxacin" "Staphylococcus" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Staphylococcus aureus" "Moxifloxacin" "Staphylococcus" "5ug" 25 25 FALSE +"EUCAST 2021" "MIC" "Staphylococcus aureus" "Moxifloxacin" "Staphylococcus" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Streptococcus agalactiae" "Moxifloxacin" "Streptococcus A,B,C,G" "5ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus agalactiae" "Moxifloxacin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus" "Moxifloxacin" "Streptococcus A,B,C,G" "5ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Moxifloxacin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus whileyi" "Moxifloxacin" "Streptococcus A,B,C,G" "5ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus whileyi" "Moxifloxacin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae" "Moxifloxacin" "Streptococcus A,B,C,G" "5ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae" "Moxifloxacin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae equisimilis" "Moxifloxacin" "Streptococcus A,B,C,G" "5ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae equisimilis" "Moxifloxacin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi" "Moxifloxacin" "Streptococcus A,B,C,G" "5ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi" "Moxifloxacin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi ruminatorum" "Moxifloxacin" "Streptococcus A,B,C,G" "5ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi ruminatorum" "Moxifloxacin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi zooepidemicus" "Moxifloxacin" "Streptococcus A,B,C,G" "5ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi zooepidemicus" "Moxifloxacin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group A" "Moxifloxacin" "Streptococcus A,B,C,G" "5ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group A" "Moxifloxacin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group B" "Moxifloxacin" "Streptococcus A,B,C,G" "5ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group B" "Moxifloxacin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group C" "Moxifloxacin" "Streptococcus A,B,C,G" "5ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group C" "Moxifloxacin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group D" "Moxifloxacin" "Streptococcus A,B,C,G" "5ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group D" "Moxifloxacin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group F" "Moxifloxacin" "Streptococcus A,B,C,G" "5ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group F" "Moxifloxacin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group G" "Moxifloxacin" "Streptococcus A,B,C,G" "5ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group G" "Moxifloxacin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group H" "Moxifloxacin" "Streptococcus A,B,C,G" "5ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group H" "Moxifloxacin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group K" "Moxifloxacin" "Streptococcus A,B,C,G" "5ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group K" "Moxifloxacin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus pneumoniae" "Moxifloxacin" "S.pneumoniae" "5ug" 22 22 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Moxifloxacin" "S.pneumoniae" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus pyogenes" "Moxifloxacin" "Streptococcus A,B,C,G" "5ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus pyogenes" "Moxifloxacin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius" "Moxifloxacin" "Streptococcus A,B,C,G" "5ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius" "Moxifloxacin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius thermophilus" "Moxifloxacin" "Streptococcus A,B,C,G" "5ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius thermophilus" "Moxifloxacin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus sanguinis" "Moxifloxacin" "Streptococcus A,B,C,G" "5ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus sanguinis" "Moxifloxacin" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Moxifloxacin" "PK PD breakpoints" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Haemophilus influenzae" "Minocycline" "H.influenzae" "30ug" 24 24 FALSE +"EUCAST 2021" "MIC" "Haemophilus influenzae" "Minocycline" "H.influenzae" 1 1 FALSE +"EUCAST 2021" "DISK" "Moraxella catarrhalis" "Minocycline" "M.catarrhalis" "30ug" 25 25 FALSE +"EUCAST 2021" "MIC" "Moraxella catarrhalis" "Minocycline" "M.catarrhalis" 1 1 FALSE +"EUCAST 2021" "MIC" "Neisseria meningitidis" "Minocycline" "N.meningitidis" 1 1 FALSE +"EUCAST 2021" "DISK" "Staphylococcus" "Minocycline" "Staphylococcus" "30ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Minocycline" "Staphylococcus" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus agalactiae" "Minocycline" "Streptococcus A,B,C,G" "30ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Streptococcus agalactiae" "Minocycline" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus" "Minocycline" "Streptococcus A,B,C,G" "30ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Minocycline" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus whileyi" "Minocycline" "Streptococcus A,B,C,G" "30ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus whileyi" "Minocycline" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae" "Minocycline" "Streptococcus A,B,C,G" "30ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae" "Minocycline" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae equisimilis" "Minocycline" "Streptococcus A,B,C,G" "30ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae equisimilis" "Minocycline" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi" "Minocycline" "Streptococcus A,B,C,G" "30ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi" "Minocycline" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi ruminatorum" "Minocycline" "Streptococcus A,B,C,G" "30ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi ruminatorum" "Minocycline" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi zooepidemicus" "Minocycline" "Streptococcus A,B,C,G" "30ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi zooepidemicus" "Minocycline" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group A" "Minocycline" "Streptococcus A,B,C,G" "30ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Streptococcus group A" "Minocycline" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group B" "Minocycline" "Streptococcus A,B,C,G" "30ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Streptococcus group B" "Minocycline" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group C" "Minocycline" "Streptococcus A,B,C,G" "30ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Streptococcus group C" "Minocycline" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group D" "Minocycline" "Streptococcus A,B,C,G" "30ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Streptococcus group D" "Minocycline" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group F" "Minocycline" "Streptococcus A,B,C,G" "30ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Streptococcus group F" "Minocycline" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group G" "Minocycline" "Streptococcus A,B,C,G" "30ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Streptococcus group G" "Minocycline" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group H" "Minocycline" "Streptococcus A,B,C,G" "30ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Streptococcus group H" "Minocycline" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group K" "Minocycline" "Streptococcus A,B,C,G" "30ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Streptococcus group K" "Minocycline" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus pneumoniae" "Minocycline" "S.pneumoniae" "30ug" 24 24 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Minocycline" "S.pneumoniae" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus pyogenes" "Minocycline" "Streptococcus A,B,C,G" "30ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Streptococcus pyogenes" "Minocycline" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius" "Minocycline" "Streptococcus A,B,C,G" "30ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius" "Minocycline" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius thermophilus" "Minocycline" "Streptococcus A,B,C,G" "30ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius thermophilus" "Minocycline" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus sanguinis" "Minocycline" "Streptococcus A,B,C,G" "30ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Streptococcus sanguinis" "Minocycline" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Actinomyces" "Metronidazole" "Anaerobes, Grampositive" 4 4 FALSE +"EUCAST 2021" "MIC" "Bacteroides" "Metronidazole" "Anaerobes, Gramnegative" 4 4 FALSE +"EUCAST 2021" "MIC" "Bifidobacterium" "Metronidazole" "Anaerobes, Grampositive" 4 4 FALSE +"EUCAST 2021" "MIC" "Bilophila" "Metronidazole" "Anaerobes, Gramnegative" 4 4 FALSE +"EUCAST 2021" "MIC" "Clostridioides" "Metronidazole" "Anaerobes, Grampositive" 4 4 FALSE +"EUCAST 2021" "MIC" "Clostridioides difficile" "Metronidazole" "C.difficile" 2 2 FALSE +"EUCAST 2021" "MIC" "Cutibacterium" "Metronidazole" "Anaerobes, Grampositive" 4 4 FALSE +"EUCAST 2021" "MIC" "Clostridium" "Metronidazole" "Anaerobes, Grampositive" 4 4 FALSE +"EUCAST 2021" "MIC" "Eubacterium" "Metronidazole" "Anaerobes, Grampositive" 4 4 FALSE +"EUCAST 2021" "MIC" "Eggerthella" "Metronidazole" "Anaerobes, Grampositive" 4 4 FALSE +"EUCAST 2021" "MIC" "Fusobacterium" "Metronidazole" "Anaerobes, Gramnegative" 4 4 FALSE +"EUCAST 2021" "MIC" "Helicobacter pylori" "Metronidazole" "H.pylori" 8 8 FALSE +"EUCAST 2021" "MIC" "Lactobacillus" "Metronidazole" "Anaerobes, Grampositive" 4 4 FALSE +"EUCAST 2021" "MIC" "Mobiluncus" "Metronidazole" "Anaerobes, Gramnegative" 4 4 FALSE +"EUCAST 2021" "MIC" "Parabacteroides" "Metronidazole" "Anaerobes, Gramnegative" 4 4 FALSE +"EUCAST 2021" "MIC" "Porphyromonas" "Metronidazole" "Anaerobes, Gramnegative" 4 4 FALSE +"EUCAST 2021" "MIC" "Propionibacterium" "Metronidazole" "Anaerobes, Grampositive" 4 4 FALSE +"EUCAST 2021" "MIC" "Prevotella" "Metronidazole" "Anaerobes, Gramnegative" 4 4 FALSE +"EUCAST 2021" "MIC" "Staphylococcus saccharolyticus" "Metronidazole" "Anaerobes, Grampositive" 4 4 FALSE +"EUCAST 2021" "DISK" "UTI" "Aerococcus sanguinicola" "Nitrofurantoin" "A.sanguinicola_A.urinae" "100ug" 16 16 TRUE +"EUCAST 2021" "MIC" "UTI" "Aerococcus sanguinicola" "Nitrofurantoin" "A.sanguinicola_A.urinae" 1 1 TRUE +"EUCAST 2021" "DISK" "UTI" "Aerococcus urinae" "Nitrofurantoin" "A.sanguinicola_A.urinae" "100ug" 16 16 TRUE +"EUCAST 2021" "MIC" "UTI" "Aerococcus urinae" "Nitrofurantoin" "A.sanguinicola_A.urinae" 1 1 TRUE +"EUCAST 2021" "DISK" "UTI" "Enterococcus faecalis" "Nitrofurantoin" "Enterococcus" "100ug" 15 15 TRUE +"EUCAST 2021" "MIC" "UTI" "Enterococcus faecalis" "Nitrofurantoin" "Enterococcus" 64 64 TRUE +"EUCAST 2021" "DISK" "UTI" "Escherichia coli" "Nitrofurantoin" "Enterobacterales" "100ug" 11 11 TRUE +"EUCAST 2021" "MIC" "UTI" "Escherichia coli" "Nitrofurantoin" "Enterobacterales" 64 64 TRUE +"EUCAST 2021" "DISK" "UTI" "Staphylococcus saprophyticus" "Nitrofurantoin" "Staphylococcus" "100ug" 13 13 TRUE +"EUCAST 2021" "MIC" "UTI" "Staphylococcus saprophyticus" "Nitrofurantoin" "Staphylococcus" 64 64 TRUE +"EUCAST 2021" "DISK" "UTI" "Streptococcus agalactiae" "Nitrofurantoin" "Streptococcus A,B,C,G" "100ug" 15 15 TRUE +"EUCAST 2021" "MIC" "UTI" "Streptococcus agalactiae" "Nitrofurantoin" "Streptococcus A,B,C,G" 64 64 TRUE +"EUCAST 2021" "DISK" "UTI" "Enterobacterales" "Norfloxacin" "Enterobacterales" "10ug" 22 22 TRUE +"EUCAST 2021" "MIC" "UTI" "Enterobacterales" "Norfloxacin" "Enterobacterales" 0.5 0.5 TRUE +"EUCAST 2021" "DISK" "UTI" "Escherichia coli" "Nitroxoline" "Enterobacterales" "30ug" 15 15 TRUE +"EUCAST 2021" "MIC" "UTI" "Escherichia coli" "Nitroxoline" "Enterobacterales" 1 1 TRUE +"EUCAST 2021" "DISK" "Enterobacterales" "Ofloxacin" "Enterobacterales" "5ug" 24 22 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Ofloxacin" "Enterobacterales" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Haemophilus influenzae" "Ofloxacin" "H.influenzae" "5ug" 30 30 FALSE +"EUCAST 2021" "MIC" "Haemophilus influenzae" "Ofloxacin" "H.influenzae" 0.06 0.06 FALSE +"EUCAST 2021" "DISK" "Moraxella catarrhalis" "Ofloxacin" "M.catarrhalis" "5ug" 28 28 FALSE +"EUCAST 2021" "MIC" "Moraxella catarrhalis" "Ofloxacin" "M.catarrhalis" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Neisseria gonorrhoeae" "Ofloxacin" "N.gonorrhoeae" 0.125 0.25 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Ofloxacin" "PK PD breakpoints" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Staphylococcus aureus" "Oritavancin" "Staphylococcus" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Streptococcus agalactiae" "Oritavancin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Oritavancin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Oritavancin" "Viridans group streptococci" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus whileyi" "Oritavancin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae" "Oritavancin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae equisimilis" "Oritavancin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi" "Oritavancin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi ruminatorum" "Oritavancin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi zooepidemicus" "Oritavancin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Streptococcus group A" "Oritavancin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Streptococcus group B" "Oritavancin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Streptococcus group C" "Oritavancin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Streptococcus group D" "Oritavancin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Streptococcus group F" "Oritavancin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Streptococcus group G" "Oritavancin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Streptococcus group H" "Oritavancin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Streptococcus group K" "Oritavancin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Streptococcus pyogenes" "Oritavancin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius" "Oritavancin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius thermophilus" "Oritavancin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Streptococcus sanguinis" "Oritavancin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Oritavancin" "PK PD breakpoints" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Aerococcus sanguinicola" "Benzylpenicillin" "A.sanguinicola_A.urinae" "1ug" 21 21 FALSE +"EUCAST 2021" "MIC" "Aerococcus sanguinicola" "Benzylpenicillin" "A.sanguinicola_A.urinae" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Aerococcus urinae" "Benzylpenicillin" "A.sanguinicola_A.urinae" "1ug" 21 21 FALSE +"EUCAST 2021" "MIC" "Aerococcus urinae" "Benzylpenicillin" "A.sanguinicola_A.urinae" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Actinomyces" "Benzylpenicillin" "Anaerobes, Grampositive" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Bacteroides" "Benzylpenicillin" "Anaerobes, Gramnegative" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Bifidobacterium" "Benzylpenicillin" "Anaerobes, Grampositive" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Bilophila" "Benzylpenicillin" "Anaerobes, Gramnegative" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Clostridioides" "Benzylpenicillin" "Anaerobes, Grampositive" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Corynebacterium" "Benzylpenicillin" "Corynebacterium" "1ug" 29 29 FALSE +"EUCAST 2021" "MIC" "Corynebacterium" "Benzylpenicillin" "Corynebacterium" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Cutibacterium" "Benzylpenicillin" "Anaerobes, Grampositive" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Clostridium" "Benzylpenicillin" "Anaerobes, Grampositive" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Eubacterium" "Benzylpenicillin" "Anaerobes, Grampositive" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Eggerthella" "Benzylpenicillin" "Anaerobes, Grampositive" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Fusobacterium" "Benzylpenicillin" "Anaerobes, Gramnegative" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Kingella kingae" "Benzylpenicillin" "K.kingae" "1ug" 25 25 FALSE +"EUCAST 2021" "MIC" "Kingella kingae" "Benzylpenicillin" "K.kingae" 0.03 0.03 FALSE +"EUCAST 2021" "MIC" "Lactobacillus" "Benzylpenicillin" "Anaerobes, Grampositive" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Listeria monocytogenes" "Benzylpenicillin" "L.monocytogenes" "1ug" 13 13 FALSE +"EUCAST 2021" "MIC" "Listeria monocytogenes" "Benzylpenicillin" "L.monocytogenes" 1 1 FALSE +"EUCAST 2021" "MIC" "Mobiluncus" "Benzylpenicillin" "Anaerobes, Gramnegative" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Neisseria gonorrhoeae" "Benzylpenicillin" "N.gonorrhoeae" 0.06 1 FALSE +"EUCAST 2021" "MIC" "Neisseria meningitidis" "Benzylpenicillin" "N.meningitidis" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Parabacteroides" "Benzylpenicillin" "Anaerobes, Gramnegative" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Porphyromonas" "Benzylpenicillin" "Anaerobes, Gramnegative" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Propionibacterium" "Benzylpenicillin" "Anaerobes, Grampositive" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Prevotella" "Benzylpenicillin" "Anaerobes, Gramnegative" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Pasteurella multocida" "Benzylpenicillin" "P.multocida" "1ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Pasteurella multocida" "Benzylpenicillin" "P.multocida" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Staphylococcus aureus" "Benzylpenicillin" "Staphylococcus" "1ug" 26 26 FALSE +"EUCAST 2021" "MIC" "Staphylococcus aureus" "Benzylpenicillin" "Staphylococcus" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Staphylococcus lugdunensis" "Benzylpenicillin" "Staphylococcus" "1ug" 26 26 FALSE +"EUCAST 2021" "MIC" "Staphylococcus lugdunensis" "Benzylpenicillin" "Staphylococcus" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "Staphylococcus saccharolyticus" "Benzylpenicillin" "Anaerobes, Grampositive" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus agalactiae" "Benzylpenicillin" "Streptococcus A,B,C,G" "1ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus agalactiae" "Benzylpenicillin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus" "Benzylpenicillin" "Streptococcus A,B,C,G" "1ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Benzylpenicillin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus whileyi" "Benzylpenicillin" "Streptococcus A,B,C,G" "1ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus whileyi" "Benzylpenicillin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae" "Benzylpenicillin" "Streptococcus A,B,C,G" "1ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae" "Benzylpenicillin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae equisimilis" "Benzylpenicillin" "Streptococcus A,B,C,G" "1ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae equisimilis" "Benzylpenicillin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi" "Benzylpenicillin" "Streptococcus A,B,C,G" "1ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi" "Benzylpenicillin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi ruminatorum" "Benzylpenicillin" "Streptococcus A,B,C,G" "1ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi ruminatorum" "Benzylpenicillin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi zooepidemicus" "Benzylpenicillin" "Streptococcus A,B,C,G" "1ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi zooepidemicus" "Benzylpenicillin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Streptococcus group A" "Benzylpenicillin" "Streptococcus A,B,C,G" "1ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus group A" "Benzylpenicillin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Streptococcus group B" "Benzylpenicillin" "Streptococcus A,B,C,G" "1ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus group B" "Benzylpenicillin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Streptococcus group C" "Benzylpenicillin" "Streptococcus A,B,C,G" "1ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus group C" "Benzylpenicillin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Streptococcus group D" "Benzylpenicillin" "Streptococcus A,B,C,G" "1ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus group D" "Benzylpenicillin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Streptococcus group F" "Benzylpenicillin" "Streptococcus A,B,C,G" "1ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus group F" "Benzylpenicillin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Streptococcus group G" "Benzylpenicillin" "Streptococcus A,B,C,G" "1ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus group G" "Benzylpenicillin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Streptococcus group H" "Benzylpenicillin" "Streptococcus A,B,C,G" "1ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus group H" "Benzylpenicillin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Streptococcus group K" "Benzylpenicillin" "Streptococcus A,B,C,G" "1ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus group K" "Benzylpenicillin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Benzylpenicillin" "S.pneumoniae" 0.06 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus pyogenes" "Benzylpenicillin" "Streptococcus A,B,C,G" "1ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus pyogenes" "Benzylpenicillin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius" "Benzylpenicillin" "Streptococcus A,B,C,G" "1ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius" "Benzylpenicillin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius thermophilus" "Benzylpenicillin" "Streptococcus A,B,C,G" "1ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius thermophilus" "Benzylpenicillin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Streptococcus sanguinis" "Benzylpenicillin" "Streptococcus A,B,C,G" "1ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus sanguinis" "Benzylpenicillin" "Streptococcus A,B,C,G" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Viridans Group Streptococcus (VGS)" "Benzylpenicillin" "Viridans group streptococci" "1ug" 18 12 FALSE +"EUCAST 2021" "MIC" "Viridans Group Streptococcus (VGS)" "Benzylpenicillin" "Viridans group streptococci" 0.25 2 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Benzylpenicillin" "PK PD breakpoints" 0.25 2 FALSE +"EUCAST 2021" "DISK" "Enterobacterales" "Piperacillin" "Enterobacterales" "30ug" 20 20 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Piperacillin" "Enterobacterales" 8 8 FALSE +"EUCAST 2021" "MIC" "Actinomyces" "Piperacillin" "Anaerobes, Grampositive" 8 1 FALSE +"EUCAST 2021" "MIC" "Bacteroides" "Piperacillin" "Anaerobes, Gramnegative" 1 1 FALSE +"EUCAST 2021" "MIC" "Bifidobacterium" "Piperacillin" "Anaerobes, Grampositive" 8 1 FALSE +"EUCAST 2021" "MIC" "Bilophila" "Piperacillin" "Anaerobes, Gramnegative" 1 1 FALSE +"EUCAST 2021" "MIC" "Clostridioides" "Piperacillin" "Anaerobes, Grampositive" 8 1 FALSE +"EUCAST 2021" "MIC" "Cutibacterium" "Piperacillin" "Anaerobes, Grampositive" 8 1 FALSE +"EUCAST 2021" "MIC" "Clostridium" "Piperacillin" "Anaerobes, Grampositive" 8 1 FALSE +"EUCAST 2021" "MIC" "Eubacterium" "Piperacillin" "Anaerobes, Grampositive" 8 1 FALSE +"EUCAST 2021" "MIC" "Eggerthella" "Piperacillin" "Anaerobes, Grampositive" 8 1 FALSE +"EUCAST 2021" "MIC" "Fusobacterium" "Piperacillin" "Anaerobes, Gramnegative" 1 1 FALSE +"EUCAST 2021" "MIC" "Lactobacillus" "Piperacillin" "Anaerobes, Grampositive" 8 1 FALSE +"EUCAST 2021" "MIC" "Mobiluncus" "Piperacillin" "Anaerobes, Gramnegative" 1 1 FALSE +"EUCAST 2021" "MIC" "Parabacteroides" "Piperacillin" "Anaerobes, Gramnegative" 1 1 FALSE +"EUCAST 2021" "MIC" "Porphyromonas" "Piperacillin" "Anaerobes, Gramnegative" 1 1 FALSE +"EUCAST 2021" "MIC" "Propionibacterium" "Piperacillin" "Anaerobes, Grampositive" 8 1 FALSE +"EUCAST 2021" "MIC" "Prevotella" "Piperacillin" "Anaerobes, Gramnegative" 1 1 FALSE +"EUCAST 2021" "DISK" "Pseudomonas" "Piperacillin" "Pseudomonas" "30ug" 50 18 FALSE +"EUCAST 2021" "MIC" "Pseudomonas" "Piperacillin" "Pseudomonas" 0.001 1 FALSE +"EUCAST 2021" "MIC" "Staphylococcus saccharolyticus" "Piperacillin" "Anaerobes, Grampositive" 8 1 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Piperacillin" "PK PD breakpoints" 8 1 FALSE +"EUCAST 2021" "MIC" "Mycobacterium tuberculosis" "Pretomanid" "M.tuberculosis" 2 2 FALSE +"EUCAST 2021" "DISK" "Enterococcus faecium" "Quinupristin/dalfopristin" "Enterococcus" "15ug" 22 20 FALSE +"EUCAST 2021" "MIC" "Enterococcus faecium" "Quinupristin/dalfopristin" "Enterococcus" 1 4 FALSE +"EUCAST 2021" "DISK" "Staphylococcus" "Quinupristin/dalfopristin" "Staphylococcus" "15ug" 21 18 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Quinupristin/dalfopristin" "Staphylococcus" 1 2 FALSE +"EUCAST 2021" "DISK" "Aerococcus sanguinicola" "Rifampicin" "A.sanguinicola_A.urinae" "5ug" 25 25 FALSE +"EUCAST 2021" "MIC" "Aerococcus sanguinicola" "Rifampicin" "A.sanguinicola_A.urinae" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Aerococcus urinae" "Rifampicin" "A.sanguinicola_A.urinae" "5ug" 25 25 FALSE +"EUCAST 2021" "MIC" "Aerococcus urinae" "Rifampicin" "A.sanguinicola_A.urinae" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Corynebacterium" "Rifampicin" "Corynebacterium" "5ug" 30 25 FALSE +"EUCAST 2021" "MIC" "Corynebacterium" "Rifampicin" "Corynebacterium" 0.06 0.5 FALSE +"EUCAST 2021" "MIC" "Helicobacter pylori" "Rifampicin" "H.pylori" 1 1 FALSE +"EUCAST 2021" "DISK" "Haemophilus influenzae" "Rifampicin" "H.influenzae" "5ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Haemophilus influenzae" "Rifampicin" "H.influenzae" 1 1 FALSE +"EUCAST 2021" "DISK" "Kingella kingae" "Rifampicin" "K.kingae" "5ug" 20 20 FALSE +"EUCAST 2021" "MIC" "Kingella kingae" "Rifampicin" "K.kingae" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Neisseria meningitidis" "Rifampicin" "N.meningitidis" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Staphylococcus" "Rifampicin" "Staphylococcus" "5ug" 26 23 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Rifampicin" "Staphylococcus" 0.06 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus agalactiae" "Rifampicin" "Streptococcus A,B,C,G" "5ug" 21 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus agalactiae" "Rifampicin" "Streptococcus A,B,C,G" 0.06 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus" "Rifampicin" "Streptococcus A,B,C,G" "5ug" 21 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Rifampicin" "Streptococcus A,B,C,G" 0.06 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus whileyi" "Rifampicin" "Streptococcus A,B,C,G" "5ug" 21 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus whileyi" "Rifampicin" "Streptococcus A,B,C,G" 0.06 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae" "Rifampicin" "Streptococcus A,B,C,G" "5ug" 21 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae" "Rifampicin" "Streptococcus A,B,C,G" 0.06 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae equisimilis" "Rifampicin" "Streptococcus A,B,C,G" "5ug" 21 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae equisimilis" "Rifampicin" "Streptococcus A,B,C,G" 0.06 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi" "Rifampicin" "Streptococcus A,B,C,G" "5ug" 21 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi" "Rifampicin" "Streptococcus A,B,C,G" 0.06 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi ruminatorum" "Rifampicin" "Streptococcus A,B,C,G" "5ug" 21 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi ruminatorum" "Rifampicin" "Streptococcus A,B,C,G" 0.06 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi zooepidemicus" "Rifampicin" "Streptococcus A,B,C,G" "5ug" 21 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi zooepidemicus" "Rifampicin" "Streptococcus A,B,C,G" 0.06 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group A" "Rifampicin" "Streptococcus A,B,C,G" "5ug" 21 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus group A" "Rifampicin" "Streptococcus A,B,C,G" 0.06 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group B" "Rifampicin" "Streptococcus A,B,C,G" "5ug" 21 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus group B" "Rifampicin" "Streptococcus A,B,C,G" 0.06 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group C" "Rifampicin" "Streptococcus A,B,C,G" "5ug" 21 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus group C" "Rifampicin" "Streptococcus A,B,C,G" 0.06 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group D" "Rifampicin" "Streptococcus A,B,C,G" "5ug" 21 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus group D" "Rifampicin" "Streptococcus A,B,C,G" 0.06 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group F" "Rifampicin" "Streptococcus A,B,C,G" "5ug" 21 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus group F" "Rifampicin" "Streptococcus A,B,C,G" 0.06 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group G" "Rifampicin" "Streptococcus A,B,C,G" "5ug" 21 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus group G" "Rifampicin" "Streptococcus A,B,C,G" 0.06 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group H" "Rifampicin" "Streptococcus A,B,C,G" "5ug" 21 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus group H" "Rifampicin" "Streptococcus A,B,C,G" 0.06 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group K" "Rifampicin" "Streptococcus A,B,C,G" "5ug" 21 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus group K" "Rifampicin" "Streptococcus A,B,C,G" 0.06 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus pneumoniae" "Rifampicin" "S.pneumoniae" "5ug" 22 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Rifampicin" "S.pneumoniae" 0.125 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus pyogenes" "Rifampicin" "Streptococcus A,B,C,G" "5ug" 21 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus pyogenes" "Rifampicin" "Streptococcus A,B,C,G" 0.06 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius" "Rifampicin" "Streptococcus A,B,C,G" "5ug" 21 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius" "Rifampicin" "Streptococcus A,B,C,G" 0.06 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius thermophilus" "Rifampicin" "Streptococcus A,B,C,G" "5ug" 21 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius thermophilus" "Rifampicin" "Streptococcus A,B,C,G" 0.06 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus sanguinis" "Rifampicin" "Streptococcus A,B,C,G" "5ug" 21 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus sanguinis" "Rifampicin" "Streptococcus A,B,C,G" 0.06 0.5 FALSE +"EUCAST 2021" "MIC" "Moraxella catarrhalis" "Roxithromycin" "M.catarrhalis" 0.5 1 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Roxithromycin" "Staphylococcus" 1 2 FALSE +"EUCAST 2021" "MIC" "Streptococcus agalactiae" "Roxithromycin" "Streptococcus A,B,C,G" 0.5 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Roxithromycin" "Streptococcus A,B,C,G" 0.5 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus whileyi" "Roxithromycin" "Streptococcus A,B,C,G" 0.5 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae" "Roxithromycin" "Streptococcus A,B,C,G" 0.5 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae equisimilis" "Roxithromycin" "Streptococcus A,B,C,G" 0.5 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi" "Roxithromycin" "Streptococcus A,B,C,G" 0.5 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi ruminatorum" "Roxithromycin" "Streptococcus A,B,C,G" 0.5 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi zooepidemicus" "Roxithromycin" "Streptococcus A,B,C,G" 0.5 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus group A" "Roxithromycin" "Streptococcus A,B,C,G" 0.5 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus group B" "Roxithromycin" "Streptococcus A,B,C,G" 0.5 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus group C" "Roxithromycin" "Streptococcus A,B,C,G" 0.5 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus group D" "Roxithromycin" "Streptococcus A,B,C,G" 0.5 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus group F" "Roxithromycin" "Streptococcus A,B,C,G" 0.5 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus group G" "Roxithromycin" "Streptococcus A,B,C,G" 0.5 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus group H" "Roxithromycin" "Streptococcus A,B,C,G" 0.5 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus group K" "Roxithromycin" "Streptococcus A,B,C,G" 0.5 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Roxithromycin" "S.pneumoniae" 0.5 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus pyogenes" "Roxithromycin" "Streptococcus A,B,C,G" 0.5 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius" "Roxithromycin" "Streptococcus A,B,C,G" 0.5 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius thermophilus" "Roxithromycin" "Streptococcus A,B,C,G" 0.5 1 FALSE +"EUCAST 2021" "MIC" "Streptococcus sanguinis" "Roxithromycin" "Streptococcus A,B,C,G" 0.5 1 FALSE +"EUCAST 2021" "DISK" "Enterobacterales" "Ampicillin/sulbactam" "Enterobacterales" "10-10ug" 14 14 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Ampicillin/sulbactam" "Enterobacterales" 8 8 FALSE +"EUCAST 2021" "MIC" "Actinomyces" "Ampicillin/sulbactam" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Bacteroides" "Ampicillin/sulbactam" "Anaerobes, Gramnegative" 4 8 FALSE +"EUCAST 2021" "MIC" "Bifidobacterium" "Ampicillin/sulbactam" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Bilophila" "Ampicillin/sulbactam" "Anaerobes, Gramnegative" 4 8 FALSE +"EUCAST 2021" "MIC" "Clostridioides" "Ampicillin/sulbactam" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Cutibacterium" "Ampicillin/sulbactam" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Clostridium" "Ampicillin/sulbactam" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Eubacterium" "Ampicillin/sulbactam" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Eggerthella" "Ampicillin/sulbactam" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Enterococcus" "Ampicillin/sulbactam" "Enterococcus" 4 8 FALSE +"EUCAST 2021" "MIC" "Fusobacterium" "Ampicillin/sulbactam" "Anaerobes, Gramnegative" 4 8 FALSE +"EUCAST 2021" "MIC" "Haemophilus influenzae" "Ampicillin/sulbactam" "H.influenzae" 1 1 FALSE +"EUCAST 2021" "MIC" "Lactobacillus" "Ampicillin/sulbactam" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Mobiluncus" "Ampicillin/sulbactam" "Anaerobes, Gramnegative" 4 8 FALSE +"EUCAST 2021" "MIC" "Moraxella catarrhalis" "Ampicillin/sulbactam" "M.catarrhalis" 1 1 FALSE +"EUCAST 2021" "MIC" "Parabacteroides" "Ampicillin/sulbactam" "Anaerobes, Gramnegative" 4 8 FALSE +"EUCAST 2021" "MIC" "Porphyromonas" "Ampicillin/sulbactam" "Anaerobes, Gramnegative" 4 8 FALSE +"EUCAST 2021" "MIC" "Propionibacterium" "Ampicillin/sulbactam" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "Prevotella" "Ampicillin/sulbactam" "Anaerobes, Gramnegative" 4 8 FALSE +"EUCAST 2021" "MIC" "Staphylococcus saccharolyticus" "Ampicillin/sulbactam" "Anaerobes, Grampositive" 4 8 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Ampicillin/sulbactam" "PK PD breakpoints" 2 8 FALSE +"EUCAST 2021" "MIC" "Neisseria gonorrhoeae" "Spectinomycin" "N.gonorrhoeae" 64 64 FALSE +"EUCAST 2021" "DISK" "Enterobacterales" "Trimethoprim/sulfamethoxazole" "Enterobacterales" "1.25-23.75ug" 14 11 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Trimethoprim/sulfamethoxazole" "Enterobacterales" 2 4 FALSE +"EUCAST 2021" "DISK" "Achromobacter xylosoxidans" "Trimethoprim/sulfamethoxazole" "A.xylosoxidans" "1.25-23.75ug" 26 26 FALSE +"EUCAST 2021" "MIC" "Achromobacter xylosoxidans" "Trimethoprim/sulfamethoxazole" "A.xylosoxidans" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Acinetobacter" "Trimethoprim/sulfamethoxazole" "Acinetobacter" "1.25-23.75ug" 14 11 FALSE +"EUCAST 2021" "MIC" "Acinetobacter" "Trimethoprim/sulfamethoxazole" "Acinetobacter" 2 4 FALSE +"EUCAST 2021" "DISK" "Aeromonas" "Trimethoprim/sulfamethoxazole" "Aeromonas" "1.25-23.75ug" 19 16 FALSE +"EUCAST 2021" "MIC" "Aeromonas" "Trimethoprim/sulfamethoxazole" "Aeromonas" 2 4 FALSE +"EUCAST 2021" "DISK" "Burkholderia pseudomallei" "Trimethoprim/sulfamethoxazole" "B.pseudomallei" "1.25-23.75ug" 50 17 FALSE +"EUCAST 2021" "MIC" "Burkholderia pseudomallei" "Trimethoprim/sulfamethoxazole" "B.pseudomallei" 0.001 4 FALSE +"EUCAST 2021" "DISK" "Haemophilus influenzae" "Trimethoprim/sulfamethoxazole" "H.influenzae" "1.25-23.75ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Haemophilus influenzae" "Trimethoprim/sulfamethoxazole" "H.influenzae" 0.5 1 FALSE +"EUCAST 2021" "DISK" "Kingella kingae" "Trimethoprim/sulfamethoxazole" "K.kingae" "1.25-23.75ug" 28 28 FALSE +"EUCAST 2021" "MIC" "Kingella kingae" "Trimethoprim/sulfamethoxazole" "K.kingae" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Listeria monocytogenes" "Trimethoprim/sulfamethoxazole" "L.monocytogenes" "1.25-23.75ug" 29 29 FALSE +"EUCAST 2021" "MIC" "Listeria monocytogenes" "Trimethoprim/sulfamethoxazole" "L.monocytogenes" 0.06 0.06 FALSE +"EUCAST 2021" "DISK" "Moraxella catarrhalis" "Trimethoprim/sulfamethoxazole" "M.catarrhalis" "1.25-23.75ug" 18 15 FALSE +"EUCAST 2021" "MIC" "Moraxella catarrhalis" "Trimethoprim/sulfamethoxazole" "M.catarrhalis" 0.5 1 FALSE +"EUCAST 2021" "DISK" "Pasteurella multocida" "Trimethoprim/sulfamethoxazole" "P.multocida" "1.25-23.75ug" 23 23 FALSE +"EUCAST 2021" "MIC" "Pasteurella multocida" "Trimethoprim/sulfamethoxazole" "P.multocida" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Stenotrophomonas maltophilia" "Trimethoprim/sulfamethoxazole" "S.maltophilia" "1.25-23.75ug" 50 16 FALSE +"EUCAST 2021" "MIC" "Stenotrophomonas maltophilia" "Trimethoprim/sulfamethoxazole" "S.maltophilia" 0.001 4 FALSE +"EUCAST 2021" "DISK" "Staphylococcus" "Trimethoprim/sulfamethoxazole" "Staphylococcus" "1.25-23.75ug" 17 14 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Trimethoprim/sulfamethoxazole" "Staphylococcus" 2 4 FALSE +"EUCAST 2021" "DISK" "Streptococcus agalactiae" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" "1.25-23.75ug" 18 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus agalactiae" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" "1.25-23.75ug" 18 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus whileyi" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" "1.25-23.75ug" 18 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus whileyi" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" "1.25-23.75ug" 18 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae equisimilis" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" "1.25-23.75ug" 18 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae equisimilis" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" "1.25-23.75ug" 18 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi ruminatorum" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" "1.25-23.75ug" 18 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi ruminatorum" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi zooepidemicus" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" "1.25-23.75ug" 18 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi zooepidemicus" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group A" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" "1.25-23.75ug" 18 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus group A" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group B" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" "1.25-23.75ug" 18 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus group B" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group C" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" "1.25-23.75ug" 18 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus group C" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group D" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" "1.25-23.75ug" 18 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus group D" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group F" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" "1.25-23.75ug" 18 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus group F" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group G" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" "1.25-23.75ug" 18 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus group G" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group H" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" "1.25-23.75ug" 18 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus group H" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group K" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" "1.25-23.75ug" 18 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus group K" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus pneumoniae" "Trimethoprim/sulfamethoxazole" "S.pneumoniae" "1.25-23.75ug" 13 10 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Trimethoprim/sulfamethoxazole" "S.pneumoniae" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus pyogenes" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" "1.25-23.75ug" 18 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus pyogenes" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" "1.25-23.75ug" 18 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius thermophilus" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" "1.25-23.75ug" 18 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius thermophilus" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus sanguinis" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" "1.25-23.75ug" 18 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus sanguinis" "Trimethoprim/sulfamethoxazole" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Enterobacterales" "Ticarcillin/clavulanic acid" "Enterobacterales" "75-10ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Ticarcillin/clavulanic acid" "Enterobacterales" 8 16 FALSE +"EUCAST 2021" "MIC" "Actinomyces" "Ticarcillin/clavulanic acid" "Anaerobes, Grampositive" 8 16 FALSE +"EUCAST 2021" "MIC" "Bacteroides" "Ticarcillin/clavulanic acid" "Anaerobes, Gramnegative" 8 16 FALSE +"EUCAST 2021" "MIC" "Bifidobacterium" "Ticarcillin/clavulanic acid" "Anaerobes, Grampositive" 8 16 FALSE +"EUCAST 2021" "MIC" "Bilophila" "Ticarcillin/clavulanic acid" "Anaerobes, Gramnegative" 8 16 FALSE +"EUCAST 2021" "MIC" "Clostridioides" "Ticarcillin/clavulanic acid" "Anaerobes, Grampositive" 8 16 FALSE +"EUCAST 2021" "MIC" "Cutibacterium" "Ticarcillin/clavulanic acid" "Anaerobes, Grampositive" 8 16 FALSE +"EUCAST 2021" "MIC" "Clostridium" "Ticarcillin/clavulanic acid" "Anaerobes, Grampositive" 8 16 FALSE +"EUCAST 2021" "MIC" "Eubacterium" "Ticarcillin/clavulanic acid" "Anaerobes, Grampositive" 8 16 FALSE +"EUCAST 2021" "MIC" "Eggerthella" "Ticarcillin/clavulanic acid" "Anaerobes, Grampositive" 8 16 FALSE +"EUCAST 2021" "MIC" "Fusobacterium" "Ticarcillin/clavulanic acid" "Anaerobes, Gramnegative" 8 16 FALSE +"EUCAST 2021" "MIC" "Lactobacillus" "Ticarcillin/clavulanic acid" "Anaerobes, Grampositive" 8 16 FALSE +"EUCAST 2021" "MIC" "Mobiluncus" "Ticarcillin/clavulanic acid" "Anaerobes, Gramnegative" 8 16 FALSE +"EUCAST 2021" "MIC" "Parabacteroides" "Ticarcillin/clavulanic acid" "Anaerobes, Gramnegative" 8 16 FALSE +"EUCAST 2021" "MIC" "Porphyromonas" "Ticarcillin/clavulanic acid" "Anaerobes, Gramnegative" 8 16 FALSE +"EUCAST 2021" "MIC" "Propionibacterium" "Ticarcillin/clavulanic acid" "Anaerobes, Grampositive" 8 16 FALSE +"EUCAST 2021" "MIC" "Prevotella" "Ticarcillin/clavulanic acid" "Anaerobes, Gramnegative" 8 16 FALSE +"EUCAST 2021" "DISK" "Pseudomonas" "Ticarcillin/clavulanic acid" "Pseudomonas" "75-10ug" 50 18 FALSE +"EUCAST 2021" "MIC" "Pseudomonas" "Ticarcillin/clavulanic acid" "Pseudomonas" 0.001 16 FALSE +"EUCAST 2021" "MIC" "Staphylococcus saccharolyticus" "Ticarcillin/clavulanic acid" "Anaerobes, Grampositive" 8 16 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Ticarcillin/clavulanic acid" "PK PD breakpoints" 8 16 FALSE +"EUCAST 2021" "DISK" "Campylobacter coli" "Tetracycline" "C.jejuni_C.coli" "30ug" 30 30 FALSE +"EUCAST 2021" "MIC" "Campylobacter coli" "Tetracycline" "C.jejuni_C.coli" 2 2 FALSE +"EUCAST 2021" "DISK" "Campylobacter jejuni" "Tetracycline" "C.jejuni_C.coli" "30ug" 30 30 FALSE +"EUCAST 2021" "MIC" "Campylobacter jejuni" "Tetracycline" "C.jejuni_C.coli" 2 2 FALSE +"EUCAST 2021" "DISK" "Corynebacterium" "Tetracycline" "Corynebacterium" "30ug" 24 24 FALSE +"EUCAST 2021" "MIC" "Corynebacterium" "Tetracycline" "Corynebacterium" 2 2 FALSE +"EUCAST 2021" "MIC" "Helicobacter pylori" "Tetracycline" "H.pylori" 1 1 FALSE +"EUCAST 2021" "DISK" "Haemophilus influenzae" "Tetracycline" "H.influenzae" "30ug" 25 22 FALSE +"EUCAST 2021" "MIC" "Haemophilus influenzae" "Tetracycline" "H.influenzae" 1 2 FALSE +"EUCAST 2021" "DISK" "Kingella kingae" "Tetracycline" "K.kingae" "30ug" 28 28 FALSE +"EUCAST 2021" "MIC" "Kingella kingae" "Tetracycline" "K.kingae" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Moraxella catarrhalis" "Tetracycline" "M.catarrhalis" "30ug" 28 25 FALSE +"EUCAST 2021" "MIC" "Moraxella catarrhalis" "Tetracycline" "M.catarrhalis" 1 2 FALSE +"EUCAST 2021" "MIC" "Neisseria gonorrhoeae" "Tetracycline" "N.gonorrhoeae" 0.5 1 FALSE +"EUCAST 2021" "MIC" "Neisseria meningitidis" "Tetracycline" "N.meningitidis" 2 2 FALSE +"EUCAST 2021" "DISK" "Staphylococcus" "Tetracycline" "Staphylococcus" "30ug" 22 19 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Tetracycline" "Staphylococcus" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus agalactiae" "Tetracycline" "Streptococcus A,B,C,G" "30ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Streptococcus agalactiae" "Tetracycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus" "Tetracycline" "Streptococcus A,B,C,G" "30ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Tetracycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus whileyi" "Tetracycline" "Streptococcus A,B,C,G" "30ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus whileyi" "Tetracycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae" "Tetracycline" "Streptococcus A,B,C,G" "30ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae" "Tetracycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae equisimilis" "Tetracycline" "Streptococcus A,B,C,G" "30ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae equisimilis" "Tetracycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi" "Tetracycline" "Streptococcus A,B,C,G" "30ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi" "Tetracycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi ruminatorum" "Tetracycline" "Streptococcus A,B,C,G" "30ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi ruminatorum" "Tetracycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi zooepidemicus" "Tetracycline" "Streptococcus A,B,C,G" "30ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi zooepidemicus" "Tetracycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group A" "Tetracycline" "Streptococcus A,B,C,G" "30ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Streptococcus group A" "Tetracycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group B" "Tetracycline" "Streptococcus A,B,C,G" "30ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Streptococcus group B" "Tetracycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group C" "Tetracycline" "Streptococcus A,B,C,G" "30ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Streptococcus group C" "Tetracycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group D" "Tetracycline" "Streptococcus A,B,C,G" "30ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Streptococcus group D" "Tetracycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group F" "Tetracycline" "Streptococcus A,B,C,G" "30ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Streptococcus group F" "Tetracycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group G" "Tetracycline" "Streptococcus A,B,C,G" "30ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Streptococcus group G" "Tetracycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group H" "Tetracycline" "Streptococcus A,B,C,G" "30ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Streptococcus group H" "Tetracycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group K" "Tetracycline" "Streptococcus A,B,C,G" "30ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Streptococcus group K" "Tetracycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus pneumoniae" "Tetracycline" "S.pneumoniae" "30ug" 25 22 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Tetracycline" "S.pneumoniae" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus pyogenes" "Tetracycline" "Streptococcus A,B,C,G" "30ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Streptococcus pyogenes" "Tetracycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius" "Tetracycline" "Streptococcus A,B,C,G" "30ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius" "Tetracycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius thermophilus" "Tetracycline" "Streptococcus A,B,C,G" "30ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius thermophilus" "Tetracycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus sanguinis" "Tetracycline" "Streptococcus A,B,C,G" "30ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Streptococcus sanguinis" "Tetracycline" "Streptococcus A,B,C,G" 1 2 FALSE +"EUCAST 2021" "DISK" "Enterococcus" "Teicoplanin" "Enterococcus" "30ug" 16 16 FALSE +"EUCAST 2021" "MIC" "Enterococcus" "Teicoplanin" "Enterococcus" 2 2 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Teicoplanin" "Staphylococcus" 4 4 FALSE +"EUCAST 2021" "MIC" "Staphylococcus aureus" "Teicoplanin" "Staphylococcus" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus agalactiae" "Teicoplanin" "Streptococcus A,B,C,G" "30ug" 15 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus agalactiae" "Teicoplanin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus" "Teicoplanin" "Streptococcus A,B,C,G" "30ug" 15 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Teicoplanin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus whileyi" "Teicoplanin" "Streptococcus A,B,C,G" "30ug" 15 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus whileyi" "Teicoplanin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae" "Teicoplanin" "Streptococcus A,B,C,G" "30ug" 15 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae" "Teicoplanin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae equisimilis" "Teicoplanin" "Streptococcus A,B,C,G" "30ug" 15 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae equisimilis" "Teicoplanin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi" "Teicoplanin" "Streptococcus A,B,C,G" "30ug" 15 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi" "Teicoplanin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi ruminatorum" "Teicoplanin" "Streptococcus A,B,C,G" "30ug" 15 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi ruminatorum" "Teicoplanin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi zooepidemicus" "Teicoplanin" "Streptococcus A,B,C,G" "30ug" 15 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi zooepidemicus" "Teicoplanin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group A" "Teicoplanin" "Streptococcus A,B,C,G" "30ug" 15 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus group A" "Teicoplanin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group B" "Teicoplanin" "Streptococcus A,B,C,G" "30ug" 15 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus group B" "Teicoplanin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group C" "Teicoplanin" "Streptococcus A,B,C,G" "30ug" 15 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus group C" "Teicoplanin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group D" "Teicoplanin" "Streptococcus A,B,C,G" "30ug" 15 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus group D" "Teicoplanin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group F" "Teicoplanin" "Streptococcus A,B,C,G" "30ug" 15 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus group F" "Teicoplanin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group G" "Teicoplanin" "Streptococcus A,B,C,G" "30ug" 15 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus group G" "Teicoplanin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group H" "Teicoplanin" "Streptococcus A,B,C,G" "30ug" 15 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus group H" "Teicoplanin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group K" "Teicoplanin" "Streptococcus A,B,C,G" "30ug" 15 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus group K" "Teicoplanin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus pneumoniae" "Teicoplanin" "S.pneumoniae" "30ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Teicoplanin" "S.pneumoniae" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus pyogenes" "Teicoplanin" "Streptococcus A,B,C,G" "30ug" 15 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus pyogenes" "Teicoplanin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius" "Teicoplanin" "Streptococcus A,B,C,G" "30ug" 15 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius" "Teicoplanin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius thermophilus" "Teicoplanin" "Streptococcus A,B,C,G" "30ug" 15 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius thermophilus" "Teicoplanin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus sanguinis" "Teicoplanin" "Streptococcus A,B,C,G" "30ug" 15 15 FALSE +"EUCAST 2021" "MIC" "Streptococcus sanguinis" "Teicoplanin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Viridans Group Streptococcus (VGS)" "Teicoplanin" "Viridans group streptococci" "30ug" 16 16 FALSE +"EUCAST 2021" "MIC" "Viridans Group Streptococcus (VGS)" "Teicoplanin" "Viridans group streptococci" 2 2 FALSE +"EUCAST 2021" "DISK" "UTI" "Escherichia coli" "Temocillin" "Enterobacterales" "30ug" 50 17 TRUE +"EUCAST 2021" "MIC" "UTI" "Escherichia coli" "Temocillin" "Enterobacterales" 0.001 1 TRUE +"EUCAST 2021" "DISK" "UTI" "Klebsiella" "Temocillin" "Enterobacterales" "30ug" 50 17 TRUE +"EUCAST 2021" "MIC" "UTI" "Klebsiella" "Temocillin" "Enterobacterales" 0.001 1 TRUE +"EUCAST 2021" "DISK" "UTI" "Proteus mirabilis" "Temocillin" "Enterobacterales" "30ug" 50 17 TRUE +"EUCAST 2021" "MIC" "UTI" "Proteus mirabilis" "Temocillin" "Enterobacterales" 0.001 1 TRUE +"EUCAST 2021" "DISK" "Citrobacter koseri" "Tigecycline" "Enterobacterales" "15ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Citrobacter koseri" "Tigecycline" "Enterobacterales" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Enterococcus faecium" "Tigecycline" "Enterococcus" "15ug" 22 22 FALSE +"EUCAST 2021" "MIC" "Enterococcus faecium" "Tigecycline" "Enterococcus" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Enterococcus faecalis" "Tigecycline" "Enterococcus" "15ug" 20 20 FALSE +"EUCAST 2021" "MIC" "Enterococcus faecalis" "Tigecycline" "Enterococcus" 0.25 0.25 FALSE +"EUCAST 2021" "DISK" "Escherichia coli" "Tigecycline" "Enterobacterales" "15ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Escherichia coli" "Tigecycline" "Enterobacterales" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Staphylococcus" "Tigecycline" "Staphylococcus" "15ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Tigecycline" "Staphylococcus" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus agalactiae" "Tigecycline" "Streptococcus A,B,C,G" "15ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus agalactiae" "Tigecycline" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus" "Tigecycline" "Streptococcus A,B,C,G" "15ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Tigecycline" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus whileyi" "Tigecycline" "Streptococcus A,B,C,G" "15ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus whileyi" "Tigecycline" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae" "Tigecycline" "Streptococcus A,B,C,G" "15ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae" "Tigecycline" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae equisimilis" "Tigecycline" "Streptococcus A,B,C,G" "15ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae equisimilis" "Tigecycline" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi" "Tigecycline" "Streptococcus A,B,C,G" "15ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi" "Tigecycline" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi ruminatorum" "Tigecycline" "Streptococcus A,B,C,G" "15ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi ruminatorum" "Tigecycline" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi zooepidemicus" "Tigecycline" "Streptococcus A,B,C,G" "15ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi zooepidemicus" "Tigecycline" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Streptococcus group A" "Tigecycline" "Streptococcus A,B,C,G" "15ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group A" "Tigecycline" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Streptococcus group B" "Tigecycline" "Streptococcus A,B,C,G" "15ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group B" "Tigecycline" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Streptococcus group C" "Tigecycline" "Streptococcus A,B,C,G" "15ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group C" "Tigecycline" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Streptococcus group D" "Tigecycline" "Streptococcus A,B,C,G" "15ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group D" "Tigecycline" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Streptococcus group F" "Tigecycline" "Streptococcus A,B,C,G" "15ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group F" "Tigecycline" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Streptococcus group G" "Tigecycline" "Streptococcus A,B,C,G" "15ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group G" "Tigecycline" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Streptococcus group H" "Tigecycline" "Streptococcus A,B,C,G" "15ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group H" "Tigecycline" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Streptococcus group K" "Tigecycline" "Streptococcus A,B,C,G" "15ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus group K" "Tigecycline" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Streptococcus pyogenes" "Tigecycline" "Streptococcus A,B,C,G" "15ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus pyogenes" "Tigecycline" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius" "Tigecycline" "Streptococcus A,B,C,G" "15ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius" "Tigecycline" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius thermophilus" "Tigecycline" "Streptococcus A,B,C,G" "15ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius thermophilus" "Tigecycline" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "Streptococcus sanguinis" "Tigecycline" "Streptococcus A,B,C,G" "15ug" 19 19 FALSE +"EUCAST 2021" "MIC" "Streptococcus sanguinis" "Tigecycline" "Streptococcus A,B,C,G" 0.125 0.125 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Tigecycline" "PK PD breakpoints" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Enterobacterales" "Ticarcillin" "Enterobacterales" "75ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Ticarcillin" "Enterobacterales" 8 1 FALSE +"EUCAST 2021" "MIC" "Actinomyces" "Ticarcillin" "Anaerobes, Grampositive" 8 1 FALSE +"EUCAST 2021" "MIC" "Bacteroides" "Ticarcillin" "Anaerobes, Gramnegative" 1 1 FALSE +"EUCAST 2021" "MIC" "Bifidobacterium" "Ticarcillin" "Anaerobes, Grampositive" 8 1 FALSE +"EUCAST 2021" "MIC" "Bilophila" "Ticarcillin" "Anaerobes, Gramnegative" 1 1 FALSE +"EUCAST 2021" "MIC" "Clostridioides" "Ticarcillin" "Anaerobes, Grampositive" 8 1 FALSE +"EUCAST 2021" "MIC" "Cutibacterium" "Ticarcillin" "Anaerobes, Grampositive" 8 1 FALSE +"EUCAST 2021" "MIC" "Clostridium" "Ticarcillin" "Anaerobes, Grampositive" 8 1 FALSE +"EUCAST 2021" "MIC" "Eubacterium" "Ticarcillin" "Anaerobes, Grampositive" 8 1 FALSE +"EUCAST 2021" "MIC" "Eggerthella" "Ticarcillin" "Anaerobes, Grampositive" 8 1 FALSE +"EUCAST 2021" "MIC" "Fusobacterium" "Ticarcillin" "Anaerobes, Gramnegative" 1 1 FALSE +"EUCAST 2021" "MIC" "Lactobacillus" "Ticarcillin" "Anaerobes, Grampositive" 8 1 FALSE +"EUCAST 2021" "MIC" "Mobiluncus" "Ticarcillin" "Anaerobes, Gramnegative" 1 1 FALSE +"EUCAST 2021" "MIC" "Parabacteroides" "Ticarcillin" "Anaerobes, Gramnegative" 1 1 FALSE +"EUCAST 2021" "MIC" "Porphyromonas" "Ticarcillin" "Anaerobes, Gramnegative" 1 1 FALSE +"EUCAST 2021" "MIC" "Propionibacterium" "Ticarcillin" "Anaerobes, Grampositive" 8 1 FALSE +"EUCAST 2021" "MIC" "Prevotella" "Ticarcillin" "Anaerobes, Gramnegative" 1 1 FALSE +"EUCAST 2021" "DISK" "Pseudomonas" "Ticarcillin" "Pseudomonas" "75ug" 50 18 FALSE +"EUCAST 2021" "MIC" "Pseudomonas" "Ticarcillin" "Pseudomonas" 0.001 1 FALSE +"EUCAST 2021" "MIC" "Staphylococcus saccharolyticus" "Ticarcillin" "Anaerobes, Grampositive" 8 1 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Ticarcillin" "PK PD breakpoints" 8 1 FALSE +"EUCAST 2021" "DISK" "Moraxella catarrhalis" "Telithromycin" "M.catarrhalis" "15ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Moraxella catarrhalis" "Telithromycin" "M.catarrhalis" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus agalactiae" "Telithromycin" "Streptococcus A,B,C,G" "15ug" 20 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus agalactiae" "Telithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus" "Telithromycin" "Streptococcus A,B,C,G" "15ug" 20 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Telithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus whileyi" "Telithromycin" "Streptococcus A,B,C,G" "15ug" 20 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus whileyi" "Telithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae" "Telithromycin" "Streptococcus A,B,C,G" "15ug" 20 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae" "Telithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae equisimilis" "Telithromycin" "Streptococcus A,B,C,G" "15ug" 20 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae equisimilis" "Telithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi" "Telithromycin" "Streptococcus A,B,C,G" "15ug" 20 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi" "Telithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi ruminatorum" "Telithromycin" "Streptococcus A,B,C,G" "15ug" 20 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi ruminatorum" "Telithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi zooepidemicus" "Telithromycin" "Streptococcus A,B,C,G" "15ug" 20 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi zooepidemicus" "Telithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group A" "Telithromycin" "Streptococcus A,B,C,G" "15ug" 20 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus group A" "Telithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group B" "Telithromycin" "Streptococcus A,B,C,G" "15ug" 20 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus group B" "Telithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group C" "Telithromycin" "Streptococcus A,B,C,G" "15ug" 20 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus group C" "Telithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group D" "Telithromycin" "Streptococcus A,B,C,G" "15ug" 20 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus group D" "Telithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group F" "Telithromycin" "Streptococcus A,B,C,G" "15ug" 20 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus group F" "Telithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group G" "Telithromycin" "Streptococcus A,B,C,G" "15ug" 20 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus group G" "Telithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group H" "Telithromycin" "Streptococcus A,B,C,G" "15ug" 20 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus group H" "Telithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group K" "Telithromycin" "Streptococcus A,B,C,G" "15ug" 20 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus group K" "Telithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus pneumoniae" "Telithromycin" "S.pneumoniae" "15ug" 23 20 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Telithromycin" "S.pneumoniae" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus pyogenes" "Telithromycin" "Streptococcus A,B,C,G" "15ug" 20 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus pyogenes" "Telithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius" "Telithromycin" "Streptococcus A,B,C,G" "15ug" 20 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius" "Telithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius thermophilus" "Telithromycin" "Streptococcus A,B,C,G" "15ug" 20 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius thermophilus" "Telithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus sanguinis" "Telithromycin" "Streptococcus A,B,C,G" "15ug" 20 17 FALSE +"EUCAST 2021" "MIC" "Streptococcus sanguinis" "Telithromycin" "Streptococcus A,B,C,G" 0.25 0.5 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Telavancin" "Staphylococcus" 0.125 0.125 FALSE +"EUCAST 2021" "DISK" "UTI" "Enterobacterales" "Trimethoprim" "Enterobacterales" "5ug" 15 15 TRUE +"EUCAST 2021" "MIC" "UTI" "Enterobacterales" "Trimethoprim" "Enterobacterales" 4 4 TRUE +"EUCAST 2021" "DISK" "UTI" "Staphylococcus" "Trimethoprim" "Staphylococcus" "5ug" 14 14 TRUE +"EUCAST 2021" "MIC" "UTI" "Staphylococcus" "Trimethoprim" "Staphylococcus" 4 4 TRUE +"EUCAST 2021" "MIC" "UTI" "Streptococcus agalactiae" "Trimethoprim" "Streptococcus A,B,C,G" 2 2 TRUE +"EUCAST 2021" "DISK" "Systemic" "Enterobacterales" "Tobramycin" "Enterobacterales" "10ug" 16 16 FALSE +"EUCAST 2021" "DISK" "UTI" "Enterobacterales" "Tobramycin" "Enterobacterales" "10ug" 16 16 TRUE +"EUCAST 2021" "MIC" "Systemic" "Enterobacterales" "Tobramycin" "Enterobacterales" 2 2 FALSE +"EUCAST 2021" "MIC" "UTI" "Enterobacterales" "Tobramycin" "Enterobacterales" 2 2 TRUE +"EUCAST 2021" "DISK" "Systemic" "Acinetobacter" "Tobramycin" "Acinetobacter" "10ug" 17 17 FALSE +"EUCAST 2021" "DISK" "UTI" "Acinetobacter" "Tobramycin" "Acinetobacter" "10ug" 17 17 TRUE +"EUCAST 2021" "MIC" "Systemic" "Acinetobacter" "Tobramycin" "Acinetobacter" 4 4 FALSE +"EUCAST 2021" "MIC" "UTI" "Acinetobacter" "Tobramycin" "Acinetobacter" 4 4 TRUE +"EUCAST 2021" "DISK" "Systemic" "Pseudomonas" "Tobramycin" "Pseudomonas" "10ug" 18 18 FALSE +"EUCAST 2021" "DISK" "UTI" "Pseudomonas" "Tobramycin" "Pseudomonas" "10ug" 18 18 TRUE +"EUCAST 2021" "MIC" "Systemic" "Pseudomonas" "Tobramycin" "Pseudomonas" 2 2 FALSE +"EUCAST 2021" "MIC" "UTI" "Pseudomonas" "Tobramycin" "Pseudomonas" 2 2 TRUE +"EUCAST 2021" "DISK" "Staphylococcus" "Tobramycin" "Staphylococcus" "10ug" 22 22 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Tobramycin" "Staphylococcus" 1 1 FALSE +"EUCAST 2021" "DISK" "Staphylococcus aureus" "Tobramycin" "Staphylococcus" "10ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Staphylococcus aureus" "Tobramycin" "Staphylococcus" 1 1 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Tobramycin" "PK PD breakpoints" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Staphylococcus" "Tedizolid" "Staphylococcus" "2ug" 21 21 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Tedizolid" "Staphylococcus" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus agalactiae" "Tedizolid" "Streptococcus A,B,C,G" "2ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus agalactiae" "Tedizolid" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus" "Tedizolid" "Streptococcus A,B,C,G" "2ug" 18 18 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus" "Tedizolid" "Viridans group streptococci" "2ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Tedizolid" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Tedizolid" "Viridans group streptococci" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus whileyi" "Tedizolid" "Streptococcus A,B,C,G" "2ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus whileyi" "Tedizolid" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae" "Tedizolid" "Streptococcus A,B,C,G" "2ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae" "Tedizolid" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae equisimilis" "Tedizolid" "Streptococcus A,B,C,G" "2ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae equisimilis" "Tedizolid" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi" "Tedizolid" "Streptococcus A,B,C,G" "2ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi" "Tedizolid" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi ruminatorum" "Tedizolid" "Streptococcus A,B,C,G" "2ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi ruminatorum" "Tedizolid" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi zooepidemicus" "Tedizolid" "Streptococcus A,B,C,G" "2ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi zooepidemicus" "Tedizolid" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group A" "Tedizolid" "Streptococcus A,B,C,G" "2ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus group A" "Tedizolid" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group B" "Tedizolid" "Streptococcus A,B,C,G" "2ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus group B" "Tedizolid" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group C" "Tedizolid" "Streptococcus A,B,C,G" "2ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus group C" "Tedizolid" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group D" "Tedizolid" "Streptococcus A,B,C,G" "2ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus group D" "Tedizolid" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group F" "Tedizolid" "Streptococcus A,B,C,G" "2ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus group F" "Tedizolid" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group G" "Tedizolid" "Streptococcus A,B,C,G" "2ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus group G" "Tedizolid" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group H" "Tedizolid" "Streptococcus A,B,C,G" "2ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus group H" "Tedizolid" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus group K" "Tedizolid" "Streptococcus A,B,C,G" "2ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus group K" "Tedizolid" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus pyogenes" "Tedizolid" "Streptococcus A,B,C,G" "2ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus pyogenes" "Tedizolid" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius" "Tedizolid" "Streptococcus A,B,C,G" "2ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius" "Tedizolid" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius thermophilus" "Tedizolid" "Streptococcus A,B,C,G" "2ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius thermophilus" "Tedizolid" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Streptococcus sanguinis" "Tedizolid" "Streptococcus A,B,C,G" "2ug" 18 18 FALSE +"EUCAST 2021" "MIC" "Streptococcus sanguinis" "Tedizolid" "Streptococcus A,B,C,G" 0.5 0.5 FALSE +"EUCAST 2021" "DISK" "Enterobacterales" "Piperacillin/tazobactam" "Enterobacterales" "30-6ug" 20 20 FALSE +"EUCAST 2021" "MIC" "Enterobacterales" "Piperacillin/tazobactam" "Enterobacterales" 8 8 FALSE +"EUCAST 2021" "DISK" "Achromobacter xylosoxidans" "Piperacillin/tazobactam" "A.xylosoxidans" "30-6ug" 26 26 FALSE +"EUCAST 2021" "MIC" "Achromobacter xylosoxidans" "Piperacillin/tazobactam" "A.xylosoxidans" 4 4 FALSE +"EUCAST 2021" "MIC" "Actinomyces" "Piperacillin/tazobactam" "Anaerobes, Grampositive" 8 16 FALSE +"EUCAST 2021" "MIC" "Bacteroides" "Piperacillin/tazobactam" "Anaerobes, Gramnegative" 8 16 FALSE +"EUCAST 2021" "MIC" "Bifidobacterium" "Piperacillin/tazobactam" "Anaerobes, Grampositive" 8 16 FALSE +"EUCAST 2021" "MIC" "Bilophila" "Piperacillin/tazobactam" "Anaerobes, Gramnegative" 8 16 FALSE +"EUCAST 2021" "MIC" "Clostridioides" "Piperacillin/tazobactam" "Anaerobes, Grampositive" 8 16 FALSE +"EUCAST 2021" "MIC" "Cutibacterium" "Piperacillin/tazobactam" "Anaerobes, Grampositive" 8 16 FALSE +"EUCAST 2021" "MIC" "Clostridium" "Piperacillin/tazobactam" "Anaerobes, Grampositive" 8 16 FALSE +"EUCAST 2021" "MIC" "Eubacterium" "Piperacillin/tazobactam" "Anaerobes, Grampositive" 8 16 FALSE +"EUCAST 2021" "MIC" "Eggerthella" "Piperacillin/tazobactam" "Anaerobes, Grampositive" 8 16 FALSE +"EUCAST 2021" "MIC" "Fusobacterium" "Piperacillin/tazobactam" "Anaerobes, Gramnegative" 8 16 FALSE +"EUCAST 2021" "DISK" "Haemophilus influenzae" "Piperacillin/tazobactam" "H.influenzae" "30-6ug" 27 27 FALSE +"EUCAST 2021" "MIC" "Haemophilus influenzae" "Piperacillin/tazobactam" "H.influenzae" 0.25 0.25 FALSE +"EUCAST 2021" "MIC" "Lactobacillus" "Piperacillin/tazobactam" "Anaerobes, Grampositive" 8 16 FALSE +"EUCAST 2021" "MIC" "Mobiluncus" "Piperacillin/tazobactam" "Anaerobes, Gramnegative" 8 16 FALSE +"EUCAST 2021" "MIC" "Parabacteroides" "Piperacillin/tazobactam" "Anaerobes, Gramnegative" 8 16 FALSE +"EUCAST 2021" "MIC" "Porphyromonas" "Piperacillin/tazobactam" "Anaerobes, Gramnegative" 8 16 FALSE +"EUCAST 2021" "MIC" "Propionibacterium" "Piperacillin/tazobactam" "Anaerobes, Grampositive" 8 16 FALSE +"EUCAST 2021" "MIC" "Prevotella" "Piperacillin/tazobactam" "Anaerobes, Gramnegative" 8 16 FALSE +"EUCAST 2021" "DISK" "Pseudomonas" "Piperacillin/tazobactam" "Pseudomonas" "30-6ug" 50 18 FALSE +"EUCAST 2021" "MIC" "Pseudomonas" "Piperacillin/tazobactam" "Pseudomonas" 0.001 16 FALSE +"EUCAST 2021" "MIC" "Staphylococcus saccharolyticus" "Piperacillin/tazobactam" "Anaerobes, Grampositive" 8 16 FALSE +"EUCAST 2021" "MIC" "(unknown name)" "Piperacillin/tazobactam" "PK PD breakpoints" 8 16 FALSE +"EUCAST 2021" "DISK" "Aerococcus sanguinicola" "Vancomycin" "A.sanguinicola_A.urinae" "5ug" 16 16 FALSE +"EUCAST 2021" "MIC" "Aerococcus sanguinicola" "Vancomycin" "A.sanguinicola_A.urinae" 1 1 FALSE +"EUCAST 2021" "DISK" "Aerococcus urinae" "Vancomycin" "A.sanguinicola_A.urinae" "5ug" 16 16 FALSE +"EUCAST 2021" "MIC" "Aerococcus urinae" "Vancomycin" "A.sanguinicola_A.urinae" 1 1 FALSE +"EUCAST 2021" "MIC" "Actinomyces" "Vancomycin" "Anaerobes, Grampositive" 2 2 FALSE +"EUCAST 2021" "DISK" "Bacillus" "Vancomycin" "Bacillus" "5ug" 10 10 FALSE +"EUCAST 2021" "MIC" "Bacillus" "Vancomycin" "Bacillus" 2 2 FALSE +"EUCAST 2021" "MIC" "Bifidobacterium" "Vancomycin" "Anaerobes, Grampositive" 2 2 FALSE +"EUCAST 2021" "MIC" "Clostridioides" "Vancomycin" "Anaerobes, Grampositive" 2 2 FALSE +"EUCAST 2021" "MIC" "Clostridioides difficile" "Vancomycin" "C.difficile" 2 2 FALSE +"EUCAST 2021" "DISK" "Corynebacterium" "Vancomycin" "Corynebacterium" "5ug" 17 17 FALSE +"EUCAST 2021" "MIC" "Corynebacterium" "Vancomycin" "Corynebacterium" 2 2 FALSE +"EUCAST 2021" "MIC" "Cutibacterium" "Vancomycin" "Anaerobes, Grampositive" 2 2 FALSE +"EUCAST 2021" "MIC" "Clostridium" "Vancomycin" "Anaerobes, Grampositive" 2 2 FALSE +"EUCAST 2021" "MIC" "Eubacterium" "Vancomycin" "Anaerobes, Grampositive" 2 2 FALSE +"EUCAST 2021" "MIC" "Eggerthella" "Vancomycin" "Anaerobes, Grampositive" 2 2 FALSE +"EUCAST 2021" "DISK" "Enterococcus" "Vancomycin" "Enterococcus" "5ug" 12 12 FALSE +"EUCAST 2021" "MIC" "Enterococcus" "Vancomycin" "Enterococcus" 4 4 FALSE +"EUCAST 2021" "MIC" "Lactobacillus" "Vancomycin" "Anaerobes, Grampositive" 2 2 FALSE +"EUCAST 2021" "MIC" "Propionibacterium" "Vancomycin" "Anaerobes, Grampositive" 2 2 FALSE +"EUCAST 2021" "MIC" "Staphylococcus" "Vancomycin" "Staphylococcus" 4 4 FALSE +"EUCAST 2021" "MIC" "Staphylococcus aureus" "Vancomycin" "Staphylococcus" 2 2 FALSE +"EUCAST 2021" "MIC" "Staphylococcus saccharolyticus" "Vancomycin" "Anaerobes, Grampositive" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus agalactiae" "Vancomycin" "Streptococcus A,B,C,G" "5ug" 13 13 FALSE +"EUCAST 2021" "MIC" "Streptococcus agalactiae" "Vancomycin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus" "Vancomycin" "Streptococcus A,B,C,G" "5ug" 13 13 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus" "Vancomycin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus anginosus whileyi" "Vancomycin" "Streptococcus A,B,C,G" "5ug" 13 13 FALSE +"EUCAST 2021" "MIC" "Streptococcus anginosus whileyi" "Vancomycin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae" "Vancomycin" "Streptococcus A,B,C,G" "5ug" 13 13 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae" "Vancomycin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus dysgalactiae equisimilis" "Vancomycin" "Streptococcus A,B,C,G" "5ug" 13 13 FALSE +"EUCAST 2021" "MIC" "Streptococcus dysgalactiae equisimilis" "Vancomycin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi" "Vancomycin" "Streptococcus A,B,C,G" "5ug" 13 13 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi" "Vancomycin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi ruminatorum" "Vancomycin" "Streptococcus A,B,C,G" "5ug" 13 13 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi ruminatorum" "Vancomycin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus equi zooepidemicus" "Vancomycin" "Streptococcus A,B,C,G" "5ug" 13 13 FALSE +"EUCAST 2021" "MIC" "Streptococcus equi zooepidemicus" "Vancomycin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group A" "Vancomycin" "Streptococcus A,B,C,G" "5ug" 13 13 FALSE +"EUCAST 2021" "MIC" "Streptococcus group A" "Vancomycin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group B" "Vancomycin" "Streptococcus A,B,C,G" "5ug" 13 13 FALSE +"EUCAST 2021" "MIC" "Streptococcus group B" "Vancomycin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group C" "Vancomycin" "Streptococcus A,B,C,G" "5ug" 13 13 FALSE +"EUCAST 2021" "MIC" "Streptococcus group C" "Vancomycin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group D" "Vancomycin" "Streptococcus A,B,C,G" "5ug" 13 13 FALSE +"EUCAST 2021" "MIC" "Streptococcus group D" "Vancomycin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group F" "Vancomycin" "Streptococcus A,B,C,G" "5ug" 13 13 FALSE +"EUCAST 2021" "MIC" "Streptococcus group F" "Vancomycin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group G" "Vancomycin" "Streptococcus A,B,C,G" "5ug" 13 13 FALSE +"EUCAST 2021" "MIC" "Streptococcus group G" "Vancomycin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group H" "Vancomycin" "Streptococcus A,B,C,G" "5ug" 13 13 FALSE +"EUCAST 2021" "MIC" "Streptococcus group H" "Vancomycin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus group K" "Vancomycin" "Streptococcus A,B,C,G" "5ug" 13 13 FALSE +"EUCAST 2021" "MIC" "Streptococcus group K" "Vancomycin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus pneumoniae" "Vancomycin" "S.pneumoniae" "5ug" 16 16 FALSE +"EUCAST 2021" "MIC" "Streptococcus pneumoniae" "Vancomycin" "S.pneumoniae" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus pyogenes" "Vancomycin" "Streptococcus A,B,C,G" "5ug" 13 13 FALSE +"EUCAST 2021" "MIC" "Streptococcus pyogenes" "Vancomycin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius" "Vancomycin" "Streptococcus A,B,C,G" "5ug" 13 13 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius" "Vancomycin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus salivarius thermophilus" "Vancomycin" "Streptococcus A,B,C,G" "5ug" 13 13 FALSE +"EUCAST 2021" "MIC" "Streptococcus salivarius thermophilus" "Vancomycin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Streptococcus sanguinis" "Vancomycin" "Streptococcus A,B,C,G" "5ug" 13 13 FALSE +"EUCAST 2021" "MIC" "Streptococcus sanguinis" "Vancomycin" "Streptococcus A,B,C,G" 2 2 FALSE +"EUCAST 2021" "DISK" "Viridans Group Streptococcus (VGS)" "Vancomycin" "Viridans group streptococci" "5ug" 15 15 FALSE +"EUCAST 2021" "MIC" "Viridans Group Streptococcus (VGS)" "Vancomycin" "Viridans group streptococci" 2 2 FALSE "EUCAST 2020" "DISK" "Enterobacterales" "Amoxicillin/clavulanic acid" "Enterobacterales" "20-10ug" 19 19 FALSE "EUCAST 2020" "DISK" "UTI" "Enterobacterales" "Amoxicillin/clavulanic acid" "Enterobacterales" "20-10ug" 16 16 TRUE "EUCAST 2020" "MIC" "Enterobacterales" "Amoxicillin/clavulanic acid" "Enterobacterales" 8 8 FALSE @@ -8064,8 +9900,6 @@ "CLSI 2019" "MIC" "(unknown name)" "Polymyxin B" "Generic CLSI rules" "300units" 2 8 FALSE "CLSI 2019" "DISK" "(unknown name)" "Penicillin/novobiocin" "Generic CLSI rules" "10units-30ug" 18 14 FALSE "CLSI 2019" "MIC" "(unknown name)" "Penicillin/novobiocin" "Generic CLSI rules" "10units-30ug" 1 4 FALSE -"CLSI 2019" "DISK" "Streptococcus pneumoniae" "Table 2G" "10ug" FALSE -"CLSI 2019" "MIC" "Oral" "Streptococcus pneumoniae" "Table 2G" 0.064 2 FALSE "CLSI 2019" "DISK" "(unknown name)" "Pirlimycin" "Generic CLSI rules" "2ug" 13 12 FALSE "CLSI 2019" "MIC" "(unknown name)" "Pirlimycin" "Generic CLSI rules" "2ug" 2 4 FALSE "CLSI 2019" "DISK" "Enterococcus" "Quinupristin/dalfopristin" "Table 2D" "15ug" 19 15 FALSE @@ -8363,6 +10197,8 @@ "CLSI 2019" "MIC" "Candida parapsilosis" "Voriconazole" "Table 1" 0.125 1 FALSE "CLSI 2019" "DISK" "Candida tropicalis" "Voriconazole" "Table 1" 17 14 FALSE "CLSI 2019" "MIC" "Candida tropicalis" "Voriconazole" "Table 1" 0.125 1 FALSE +"CLSI 2019" "DISK" "Streptococcus pneumoniae" "Phenoxymethylpenicillin" "Table 2G" "10ug" FALSE +"CLSI 2019" "MIC" "Oral" "Streptococcus pneumoniae" "Phenoxymethylpenicillin" "Table 2G" 0.064 2 FALSE "CLSI 2018" "DISK" "Aeromonas" "Amoxicillin/clavulanic acid" "M45 Table 2" "20ug" 18 13 FALSE "CLSI 2018" "MIC" "Aeromonas" "Amoxicillin/clavulanic acid" "M45 Table 2" 8 32 FALSE "CLSI 2018" "MIC" "Aggregatibacter" "Amoxicillin/clavulanic acid" "M45 Table 7" 4 8 FALSE @@ -9403,8 +11239,6 @@ "CLSI 2018" "MIC" "(unknown name)" "Polymyxin B" "Generic CLSI rules" "300units" 2 8 FALSE "CLSI 2018" "DISK" "(unknown name)" "Penicillin/novobiocin" "Generic CLSI rules" "10units-30ug" 18 14 FALSE "CLSI 2018" "MIC" "(unknown name)" "Penicillin/novobiocin" "Generic CLSI rules" "10units-30ug" 1 4 FALSE -"CLSI 2018" "DISK" "Streptococcus pneumoniae" "Table 2G" "10ug" FALSE -"CLSI 2018" "MIC" "Oral" "Streptococcus pneumoniae" "Table 2G" 0.064 2 FALSE "CLSI 2018" "DISK" "(unknown name)" "Pirlimycin" "Generic CLSI rules" "2ug" 13 12 FALSE "CLSI 2018" "MIC" "(unknown name)" "Pirlimycin" "Generic CLSI rules" "2ug" 2 4 FALSE "CLSI 2018" "DISK" "Enterococcus" "Quinupristin/dalfopristin" "Table 2D" "15ug" 19 15 FALSE @@ -9681,6 +11515,8 @@ "CLSI 2018" "DISK" "Viridans Group Streptococcus (VGS)" "Vancomycin" "Table 2H-2" "30ug" 17 FALSE "CLSI 2018" "MIC" "Viridans Group Streptococcus (VGS)" "Vancomycin" "Table 2H-2" 1 FALSE "CLSI 2018" "MIC" "(unknown name)" "Vancomycin" "Generic CLSI rules" "30ug" 4 32 FALSE +"CLSI 2018" "DISK" "Streptococcus pneumoniae" "Phenoxymethylpenicillin" "Table 2G" "10ug" FALSE +"CLSI 2018" "MIC" "Oral" "Streptococcus pneumoniae" "Phenoxymethylpenicillin" "Table 2G" 0.064 2 FALSE "CLSI 2017" "DISK" "Aeromonas" "Amoxicillin/clavulanic acid" "M45 Table 2" "20ug" 18 13 FALSE "CLSI 2017" "MIC" "Aeromonas" "Amoxicillin/clavulanic acid" "M45 Table 2" 8 32 FALSE "CLSI 2017" "MIC" "Aggregatibacter" "Amoxicillin/clavulanic acid" "M45 Table 7" 4 8 FALSE @@ -10708,8 +12544,6 @@ "CLSI 2017" "MIC" "(unknown name)" "Polymyxin B" "Generic CLSI rules" "300units" 2 8 FALSE "CLSI 2017" "DISK" "(unknown name)" "Penicillin/novobiocin" "Generic CLSI rules" "10units-30ug" 18 14 FALSE "CLSI 2017" "MIC" "(unknown name)" "Penicillin/novobiocin" "Generic CLSI rules" "10units-30ug" 1 4 FALSE -"CLSI 2017" "DISK" "Streptococcus pneumoniae" "Table 2G" "10ug" FALSE -"CLSI 2017" "MIC" "Oral" "Streptococcus pneumoniae" "Table 2G" 0.064 2 FALSE "CLSI 2017" "DISK" "(unknown name)" "Pirlimycin" "Generic CLSI rules" "2ug" 13 12 FALSE "CLSI 2017" "MIC" "(unknown name)" "Pirlimycin" "Generic CLSI rules" "2ug" 2 4 FALSE "CLSI 2017" "DISK" "Enterococcus" "Quinupristin/dalfopristin" "Table 2D" "15ug" 19 15 FALSE @@ -10984,6 +12818,8 @@ "CLSI 2017" "DISK" "Viridans Group Streptococcus (VGS)" "Vancomycin" "Table 2H-2" "30ug" 17 FALSE "CLSI 2017" "MIC" "Viridans Group Streptococcus (VGS)" "Vancomycin" "Table 2H-2" 1 FALSE "CLSI 2017" "MIC" "(unknown name)" "Vancomycin" "Generic CLSI rules" "30ug" 4 32 FALSE +"CLSI 2017" "DISK" "Streptococcus pneumoniae" "Phenoxymethylpenicillin" "Table 2G" "10ug" FALSE +"CLSI 2017" "MIC" "Oral" "Streptococcus pneumoniae" "Phenoxymethylpenicillin" "Table 2G" 0.064 2 FALSE "CLSI 2016" "DISK" "Aeromonas" "Amoxicillin/clavulanic acid" "M45 Table 2" "20ug" 18 13 FALSE "CLSI 2016" "MIC" "Aeromonas" "Amoxicillin/clavulanic acid" "M45 Table 2" 8 32 FALSE "CLSI 2016" "MIC" "Aggregatibacter" "Amoxicillin/clavulanic acid" "M45 Table 7" 4 8 FALSE @@ -12013,8 +13849,6 @@ "CLSI 2016" "MIC" "(unknown name)" "Polymyxin B" "Generic CLSI rules" "300units" 2 8 FALSE "CLSI 2016" "DISK" "(unknown name)" "Penicillin/novobiocin" "Generic CLSI rules" "10units-30ug" 18 14 FALSE "CLSI 2016" "MIC" "(unknown name)" "Penicillin/novobiocin" "Generic CLSI rules" "10units-30ug" 1 4 FALSE -"CLSI 2016" "DISK" "Streptococcus pneumoniae" "Table 2G" "10ug" FALSE -"CLSI 2016" "MIC" "Oral" "Streptococcus pneumoniae" "Table 2G" 0.064 2 FALSE "CLSI 2016" "DISK" "(unknown name)" "Pirlimycin" "Generic CLSI rules" "2ug" 13 12 FALSE "CLSI 2016" "MIC" "(unknown name)" "Pirlimycin" "Generic CLSI rules" "2ug" 2 4 FALSE "CLSI 2016" "DISK" "Enterococcus" "Quinupristin/dalfopristin" "Table 2D" "15ug" 19 15 FALSE @@ -12289,6 +14123,8 @@ "CLSI 2016" "DISK" "Viridans Group Streptococcus (VGS)" "Vancomycin" "Table 2H-2" "30ug" 17 FALSE "CLSI 2016" "MIC" "Viridans Group Streptococcus (VGS)" "Vancomycin" "Table 2H-2" 1 FALSE "CLSI 2016" "MIC" "(unknown name)" "Vancomycin" "Generic CLSI rules" "30ug" 4 32 FALSE +"CLSI 2016" "DISK" "Streptococcus pneumoniae" "Phenoxymethylpenicillin" "Table 2G" "10ug" FALSE +"CLSI 2016" "MIC" "Oral" "Streptococcus pneumoniae" "Phenoxymethylpenicillin" "Table 2G" 0.064 2 FALSE "CLSI 2015" "DISK" "Aeromonas" "Amoxicillin/clavulanic acid" "M45 Table 2" "20ug" 18 13 FALSE "CLSI 2015" "MIC" "Aeromonas" "Amoxicillin/clavulanic acid" "M45 Table 2" 8 32 FALSE "CLSI 2015" "MIC" "Aggregatibacter" "Amoxicillin/clavulanic acid" "M45 Table 7" 4 8 FALSE @@ -13315,8 +15151,6 @@ "CLSI 2015" "MIC" "(unknown name)" "Polymyxin B" "Generic CLSI rules" "300units" 2 8 FALSE "CLSI 2015" "DISK" "(unknown name)" "Penicillin/novobiocin" "Generic CLSI rules" "10units-30ug" 18 14 FALSE "CLSI 2015" "MIC" "(unknown name)" "Penicillin/novobiocin" "Generic CLSI rules" "10units-30ug" 1 4 FALSE -"CLSI 2015" "DISK" "Streptococcus pneumoniae" "Table 2G" "10ug" FALSE -"CLSI 2015" "MIC" "Oral" "Streptococcus pneumoniae" "Table 2G" 0.064 2 FALSE "CLSI 2015" "DISK" "(unknown name)" "Pirlimycin" "Generic CLSI rules" "2ug" 13 12 FALSE "CLSI 2015" "MIC" "(unknown name)" "Pirlimycin" "Generic CLSI rules" "2ug" 2 4 FALSE "CLSI 2015" "DISK" "Enterococcus" "Quinupristin/dalfopristin" "Table 2D" "15ug" 19 15 FALSE @@ -13588,6 +15422,8 @@ "CLSI 2015" "DISK" "Viridans Group Streptococcus (VGS)" "Vancomycin" "Table 2H-2" "30ug" 17 FALSE "CLSI 2015" "MIC" "Viridans Group Streptococcus (VGS)" "Vancomycin" "Table 2H-2" 1 FALSE "CLSI 2015" "MIC" "(unknown name)" "Vancomycin" "Generic CLSI rules" "30ug" 4 32 FALSE +"CLSI 2015" "DISK" "Streptococcus pneumoniae" "Phenoxymethylpenicillin" "Table 2G" "10ug" FALSE +"CLSI 2015" "MIC" "Oral" "Streptococcus pneumoniae" "Phenoxymethylpenicillin" "Table 2G" 0.064 2 FALSE "CLSI 2014" "DISK" "Aeromonas" "Amoxicillin/clavulanic acid" "M45 Table 2" "20ug" 18 13 FALSE "CLSI 2014" "MIC" "Aeromonas" "Amoxicillin/clavulanic acid" "M45 Table 2" 8 32 FALSE "CLSI 2014" "MIC" "Aggregatibacter" "Amoxicillin/clavulanic acid" "M45 Table 7" 4 8 FALSE @@ -14611,8 +16447,6 @@ "CLSI 2014" "MIC" "(unknown name)" "Polymyxin B" "Generic CLSI rules" "300units" 2 8 FALSE "CLSI 2014" "DISK" "(unknown name)" "Penicillin/novobiocin" "Generic CLSI rules" "10units-30ug" 18 14 FALSE "CLSI 2014" "MIC" "(unknown name)" "Penicillin/novobiocin" "Generic CLSI rules" "10units-30ug" 1 4 FALSE -"CLSI 2014" "DISK" "Streptococcus pneumoniae" "Table 2G" "10ug" FALSE -"CLSI 2014" "MIC" "Oral" "Streptococcus pneumoniae" "Table 2G" 0.064 2 FALSE "CLSI 2014" "DISK" "(unknown name)" "Pirlimycin" "Generic CLSI rules" "2ug" 13 12 FALSE "CLSI 2014" "MIC" "(unknown name)" "Pirlimycin" "Generic CLSI rules" "2ug" 2 4 FALSE "CLSI 2014" "DISK" "Enterococcus" "Quinupristin/dalfopristin" "Table 2D" "15ug" 19 15 FALSE @@ -14881,6 +16715,8 @@ "CLSI 2014" "DISK" "Viridans Group Streptococcus (VGS)" "Vancomycin" "Table 2H-2" "30ug" 17 FALSE "CLSI 2014" "MIC" "Viridans Group Streptococcus (VGS)" "Vancomycin" "Table 2H-2" 1 FALSE "CLSI 2014" "MIC" "(unknown name)" "Vancomycin" "Generic CLSI rules" "30ug" 4 32 FALSE +"CLSI 2014" "DISK" "Streptococcus pneumoniae" "Phenoxymethylpenicillin" "Table 2G" "10ug" FALSE +"CLSI 2014" "MIC" "Oral" "Streptococcus pneumoniae" "Phenoxymethylpenicillin" "Table 2G" 0.064 2 FALSE "CLSI 2013" "DISK" "Aeromonas" "Amoxicillin/clavulanic acid" "M45 Table 2" "20ug" 18 13 FALSE "CLSI 2013" "MIC" "Aeromonas" "Amoxicillin/clavulanic acid" "M45 Table 2" 8 32 FALSE "CLSI 2013" "MIC" "Aggregatibacter" "Amoxicillin/clavulanic acid" "M45 Table 7" 4 8 FALSE @@ -15899,8 +17735,6 @@ "CLSI 2013" "MIC" "(unknown name)" "Polymyxin B" "Generic CLSI rules" "300units" 2 8 FALSE "CLSI 2013" "DISK" "(unknown name)" "Penicillin/novobiocin" "Generic CLSI rules" "10units-30ug" 18 14 FALSE "CLSI 2013" "MIC" "(unknown name)" "Penicillin/novobiocin" "Generic CLSI rules" "10units-30ug" 1 4 FALSE -"CLSI 2013" "DISK" "Streptococcus pneumoniae" "Table 2G" "10ug" FALSE -"CLSI 2013" "MIC" "Oral" "Streptococcus pneumoniae" "Table 2G" 0.064 2 FALSE "CLSI 2013" "DISK" "(unknown name)" "Pirlimycin" "Generic CLSI rules" "2ug" 13 12 FALSE "CLSI 2013" "MIC" "(unknown name)" "Pirlimycin" "Generic CLSI rules" "2ug" 2 4 FALSE "CLSI 2013" "DISK" "Enterococcus" "Quinupristin/dalfopristin" "Table 2D" "15ug" 19 15 FALSE @@ -16169,6 +18003,8 @@ "CLSI 2013" "DISK" "Viridans Group Streptococcus (VGS)" "Vancomycin" "Table 2H-2" "30ug" 17 FALSE "CLSI 2013" "MIC" "Viridans Group Streptococcus (VGS)" "Vancomycin" "Table 2H-2" 1 FALSE "CLSI 2013" "MIC" "(unknown name)" "Vancomycin" "Generic CLSI rules" "30ug" 4 32 FALSE +"CLSI 2013" "DISK" "Streptococcus pneumoniae" "Phenoxymethylpenicillin" "Table 2G" "10ug" FALSE +"CLSI 2013" "MIC" "Oral" "Streptococcus pneumoniae" "Phenoxymethylpenicillin" "Table 2G" 0.064 2 FALSE "CLSI 2012" "DISK" "Aeromonas" "Amoxicillin/clavulanic acid" "M45 Table 2" "20ug" 18 13 FALSE "CLSI 2012" "MIC" "Aeromonas" "Amoxicillin/clavulanic acid" "M45 Table 2" 8 32 FALSE "CLSI 2012" "MIC" "Aggregatibacter" "Amoxicillin/clavulanic acid" "M45 Table 7" 4 8 FALSE @@ -17167,8 +19003,6 @@ "CLSI 2012" "MIC" "(unknown name)" "Polymyxin B" "Generic CLSI rules" "300units" 2 8 FALSE "CLSI 2012" "DISK" "(unknown name)" "Penicillin/novobiocin" "Generic CLSI rules" "10units-30ug" 18 14 FALSE "CLSI 2012" "MIC" "(unknown name)" "Penicillin/novobiocin" "Generic CLSI rules" "10units-30ug" 1 4 FALSE -"CLSI 2012" "DISK" "Streptococcus pneumoniae" "Table 2G" "10ug" FALSE -"CLSI 2012" "MIC" "Oral" "Streptococcus pneumoniae" "Table 2G" 0.064 2 FALSE "CLSI 2012" "DISK" "(unknown name)" "Pirlimycin" "Generic CLSI rules" "2ug" 13 12 FALSE "CLSI 2012" "MIC" "(unknown name)" "Pirlimycin" "Generic CLSI rules" "2ug" 2 4 FALSE "CLSI 2012" "DISK" "Enterococcus" "Quinupristin/dalfopristin" "Table 2D" "15ug" 19 15 FALSE @@ -17436,6 +19270,8 @@ "CLSI 2012" "DISK" "Viridans Group Streptococcus (VGS)" "Vancomycin" "Table 2H-2" "30ug" 17 FALSE "CLSI 2012" "MIC" "Viridans Group Streptococcus (VGS)" "Vancomycin" "Table 2H-2" 1 FALSE "CLSI 2012" "MIC" "(unknown name)" "Vancomycin" "Generic CLSI rules" "30ug" 4 32 FALSE +"CLSI 2012" "DISK" "Streptococcus pneumoniae" "Phenoxymethylpenicillin" "Table 2G" "10ug" FALSE +"CLSI 2012" "MIC" "Oral" "Streptococcus pneumoniae" "Phenoxymethylpenicillin" "Table 2G" 0.064 2 FALSE "CLSI 2011" "DISK" "Aeromonas" "Amoxicillin/clavulanic acid" "20ug" 18 13 FALSE "CLSI 2011" "MIC" "Aeromonas" "Amoxicillin/clavulanic acid" 8 32 FALSE "CLSI 2011" "MIC" "Aggregatibacter" "Amoxicillin/clavulanic acid" 4 8 FALSE @@ -18236,8 +20072,6 @@ "CLSI 2011" "MIC" "(unknown name)" "Polymyxin B" "Generic CLSI rules" "300units" 2 8 FALSE "CLSI 2011" "DISK" "(unknown name)" "Penicillin/novobiocin" "Generic CLSI rules" "10units-30ug" 18 14 FALSE "CLSI 2011" "MIC" "(unknown name)" "Penicillin/novobiocin" "Generic CLSI rules" "10units-30ug" 1 4 FALSE -"CLSI 2011" "DISK" "Streptococcus pneumoniae" "10ug" FALSE -"CLSI 2011" "MIC" "Oral" "Streptococcus pneumoniae" 0.064 2 FALSE "CLSI 2011" "DISK" "(unknown name)" "Pirlimycin" "Generic CLSI rules" "2ug" 13 12 FALSE "CLSI 2011" "MIC" "(unknown name)" "Pirlimycin" "Generic CLSI rules" "2ug" 2 4 FALSE "CLSI 2011" "DISK" "Streptococcus" "Quinupristin/dalfopristin" "15ug" 19 15 FALSE @@ -18449,6 +20283,8 @@ "CLSI 2011" "DISK" "Viridans Group Streptococcus (VGS)" "Vancomycin" "30ug" 17 FALSE "CLSI 2011" "MIC" "Viridans Group Streptococcus (VGS)" "Vancomycin" 1 FALSE "CLSI 2011" "MIC" "(unknown name)" "Vancomycin" "Generic CLSI rules" "30ug" 4 32 FALSE +"CLSI 2011" "DISK" "Streptococcus pneumoniae" "Phenoxymethylpenicillin" "10ug" FALSE +"CLSI 2011" "MIC" "Oral" "Streptococcus pneumoniae" "Phenoxymethylpenicillin" 0.064 2 FALSE "CLSI 2010" "DISK" "(unknown name)" "Amoxicillin/clavulanic acid" "Generic CLSI rules" "20-10ug" 18 13 FALSE "CLSI 2010" "MIC" "(unknown name)" "Amoxicillin/clavulanic acid" "Generic CLSI rules" "20-10ug" 8 32 FALSE "CLSI 2010" "DISK" "(unknown name)" "Amikacin" "Generic CLSI rules" "30ug" 17 14 FALSE diff --git a/data-raw/rsi_translation.xlsx b/data-raw/rsi_translation.xlsx index f2f83c6b..15b91143 100644 Binary files a/data-raw/rsi_translation.xlsx and b/data-raw/rsi_translation.xlsx differ diff --git a/data-raw/translations.tsv b/data-raw/translations.tsv index f5130755..d6c9ada5 100644 --- a/data-raw/translations.tsv +++ b/data-raw/translations.tsv @@ -19,7 +19,8 @@ de CoPS KPS TRUE FALSE de Gram-negative Gramnegativ FALSE FALSE de Gram-positive Grampositiv FALSE FALSE de Bacteria Bakterien FALSE FALSE -de Fungi Hefen/Pilze FALSE FALSE +de Fungi Pilze FALSE FALSE +de Yeasts Hefen FALSE FALSE de Protozoa Protozoen FALSE FALSE de biogroup Biogruppe FALSE FALSE de biotype Biotyp FALSE FALSE @@ -49,8 +50,9 @@ nl CoPS CPS TRUE FALSE nl Gram-negative Gram-negatief FALSE FALSE nl Gram-positive Gram-positief FALSE FALSE nl Bacteria Bacteriën FALSE FALSE -nl Fungi Schimmels/gisten FALSE FALSE -nl Protozoa protozoën FALSE FALSE +nl Fungi Schimmels FALSE FALSE +nl Yeasts Gisten FALSE FALSE +nl Protozoa Protozoën FALSE FALSE nl biogroup biogroep FALSE FALSE nl vegetative vegetatief FALSE FALSE nl ([([ ]*?)group \\1groep FALSE FALSE @@ -83,6 +85,7 @@ es Gram-negative Gram negativo FALSE FALSE es Gram-positive Gram positivo FALSE FALSE es Bacteria Bacterias FALSE FALSE es Fungi Hongos FALSE FALSE +es Yeasts Levaduras FALSE FALSE es Protozoa Protozoarios FALSE FALSE es biogroup biogrupo FALSE FALSE es biotype biotipo FALSE FALSE @@ -110,7 +113,8 @@ it unknown rank grado sconosciuto FALSE FALSE it Gram-negative Gram negativo FALSE FALSE it Gram-positive Gram positivo FALSE FALSE it Bacteria Batteri FALSE FALSE -it Fungi Fungo FALSE FALSE +it Fungi Funghi FALSE FALSE +it Yeasts Lieviti FALSE FALSE it Protozoa Protozoi FALSE FALSE it biogroup biogruppo FALSE FALSE it biotype biotipo FALSE FALSE @@ -139,6 +143,7 @@ fr Gram-negative Gram négatif FALSE FALSE fr Gram-positive Gram positif FALSE FALSE fr Bacteria Bactéries FALSE FALSE fr Fungi Champignons FALSE FALSE +fr Yeasts Levures FALSE FALSE fr Protozoa Protozoaires FALSE FALSE fr biogroup biogroupe FALSE FALSE fr vegetative végétatif FALSE FALSE @@ -166,6 +171,7 @@ pt Gram-negative Gram negativo FALSE FALSE pt Gram-positive Gram positivo FALSE FALSE pt Bacteria Bactérias FALSE FALSE pt Fungi Fungos FALSE FALSE +pt Yeasts Leveduras FALSE FALSE pt Protozoa Protozoários FALSE FALSE pt biogroup biogrupo FALSE FALSE pt biotype biótipo FALSE FALSE diff --git a/data-raw/v_11.0_Breakpoint_Tables.xlsx b/data-raw/v_11.0_Breakpoint_Tables.xlsx new file mode 100644 index 00000000..a2c7efcb Binary files /dev/null and b/data-raw/v_11.0_Breakpoint_Tables.xlsx differ diff --git a/data/antibiotics.rda b/data/antibiotics.rda index c10caf70..ebc9714e 100755 Binary files a/data/antibiotics.rda and b/data/antibiotics.rda differ diff --git a/data/dosage.rda b/data/dosage.rda new file mode 100644 index 00000000..934c3496 Binary files /dev/null and b/data/dosage.rda differ diff --git a/data/microorganisms.codes.rda b/data/microorganisms.codes.rda index 5fecdf03..710301a3 100644 Binary files a/data/microorganisms.codes.rda and b/data/microorganisms.codes.rda differ diff --git a/data/rsi_translation.rda b/data/rsi_translation.rda index 065a44a3..6a8ea635 100644 Binary files a/data/rsi_translation.rda and b/data/rsi_translation.rda differ diff --git a/docs/404.html b/docs/404.html index 44b8b7d2..34eaa2e8 100644 --- a/docs/404.html +++ b/docs/404.html @@ -81,7 +81,7 @@ AMR (for R) - 1.5.0 + 1.5.0.9000 diff --git a/docs/LICENSE-text.html b/docs/LICENSE-text.html index d1028e1d..4365f2d3 100644 --- a/docs/LICENSE-text.html +++ b/docs/LICENSE-text.html @@ -81,7 +81,7 @@ AMR (for R) - 1.5.0 + 1.5.0.9000 diff --git a/docs/articles/index.html b/docs/articles/index.html index 0047bd5d..342a7e77 100644 --- a/docs/articles/index.html +++ b/docs/articles/index.html @@ -81,7 +81,7 @@ AMR (for R) - 1.5.0 + 1.5.0.9000 diff --git a/docs/authors.html b/docs/authors.html index 199230b9..46f017c3 100644 --- a/docs/authors.html +++ b/docs/authors.html @@ -81,7 +81,7 @@ AMR (for R) - 1.5.0 + 1.5.0.9000 diff --git a/docs/index.html b/docs/index.html index f328198d..f9c20886 100644 --- a/docs/index.html +++ b/docs/index.html @@ -43,7 +43,7 @@ AMR (for R) - 1.5.0 + 1.5.0.9000 diff --git a/docs/news/index.html b/docs/news/index.html index eea0d198..703d0672 100644 --- a/docs/news/index.html +++ b/docs/news/index.html @@ -81,7 +81,7 @@ AMR (for R) - 1.5.0 + 1.5.0.9000 @@ -236,18 +236,69 @@ Source: NEWS.md -
-

-AMR 1.5.0 Unreleased +
+

+AMR 1.5.0.9000 Unreleased

-

Note: the rules of ‘EUCAST Clinical Breakpoints v11.0 (2021)’ will be added in the next release, to be expected in February/March 2021.

+
+

+Last updated: 12 January 2021 +

+

Note: the rules of ‘EUCAST Clinical Breakpoints v11.0 (2021)’ will also be added in this next release, to be expected in February/March 2021.

New

    +

  • Support for EUCAST Clinical Breakpoints v11.0 (2021), effective in the eucast_rules() function and in as.rsi() to interpret MIC and disk diffusion values. This is now the default guideline in this package.

    • +

  • Function eucast_dosage() to to get advised dosages of a certain bug-drug combination based on EUCAST dosage data

    • +

  • Data set dosage to fuel the new eucast_dosage() function and to make this data available in a structured way

    • +

  • Function isolate_identifier(), which will paste a microorganism code with all antimicrobial results of a data set into one string for each row. This is useful to compare isolates, e.g. between institutions or regions, when there is no genotyping available.

    • +
  • +

    Function mo_is_yeast(), which determines whether a microorganism is a member of the taxonomic class Saccharomycetes or the taxonomic order Saccharomycetales:

    +
    +
+mo_kingdom(c("Aspergillus", "Candida"))
+#> [1] "Fungi" "Fungi"
+
+mo_is_yeast(c("Aspergillus", "Candida"))
+#> [1] FALSE  TRUE
+
+# usage for filtering data:
+example_isolates[which(mo_is_yeast()), ]   # base R
+example_isolates %>% filter(mo_is_yeast()) # dplyr
    +

    The mo_type() function has also been updated to reflect this change:

    +
    +
+mo_type(c("Aspergillus", "Candida"))
+# [1] "Fungi"  "Yeasts"
+mo_type(c("Aspergillus", "Candida"), language = "es") # also supported: de, nl, fr, it, pt
+#> [1] "Hongos"    "Levaduras"
    +
    • +
+
+
+

+Changed

+ +
+
+
+
+

+AMR 1.5.0 2021-01-06 +

+
+

+New

+
-
+

-Changed

+Changed

-
+
 
 # to select first isolates that are Gram-negative 
 # and view results of cephalosporins and aminoglycosides:
@@ -313,7 +364,7 @@
 
 
  • 
 
    For antibiotic selection functions (such as cephalosporins(), aminoglycosides()) to select columns based on a certain antibiotic group, the dependency on the tidyselect package was removed, meaning that they can now also be used without the need to have this package installed and now also work in base R function calls (they rely on R 3.2 or later):
    
-
    +
     
 # above example in base R:
 example_isolates[which(first_isolate() & mo_is_gram_negative()),
@@ -355,16 +406,16 @@
 
    
 AMR 1.4.0 2020-10-08 
 
    
-
    
+
    
 
    
-New
    
+New
 
      
 
    • Support for ‘EUCAST Expert Rules’ / ‘EUCAST Intrinsic Resistance and Unusual Phenotypes’ version 3.2 of May 2020. With this addition to the previously implemented version 3.1 of 2016, the eucast_rules() function can now correct for more than 180 different antibiotics and the mdro() function can determine multidrug resistance based on more than 150 different antibiotics. All previously implemented versions of the EUCAST rules are now maintained and kept available in this package. The eucast_rules() function consequently gained the arguments version_breakpoints (at the moment defaults to v10.0, 2020) and version_expertrules (at the moment defaults to v3.2, 2020). The example_isolates data set now also reflects the change from v3.1 to v3.2. The mdro() function now accepts guideline == "EUCAST3.1" and guideline == "EUCAST3.2".
      • 
 
    • A new vignette and website page with info about all our public and freely available data sets, that can be downloaded as flat files or in formats for use in R, SPSS, SAS, Stata and Excel: https://msberends.github.io/AMR/articles/datasets.html
      • 
 
    • 
 
      Data set intrinsic_resistant. This data set contains all bug-drug combinations where the ‘bug’ is intrinsic resistant to the ‘drug’ according to the latest EUCAST insights. It contains just two columns: microorganism and antibiotic.
      
 
      Curious about which enterococci are actually intrinsic resistant to vancomycin?
      
-
      +
       
 library(AMR)
 library(dplyr)
@@ -377,9 +428,9 @@
 
    • Support for skimming classes <rsi>, <mic>, <disk> and <mo> with the skimr package
      • 
 
    
 
    
-
    
+
    
 
    
-Changed
    
+Changed
 
      
 
    • Although advertised that this package should work under R 3.0.0, we still had a dependency on R 3.6.0. This is fixed, meaning that our package should now work under R 3.0.0.
      • 
 
    • 
@@ -387,7 +438,7 @@
 
        
 
      • 
 
        Support for using dplyr’s across() to interpret MIC values or disk zone diameters, which also automatically determines the column with microorganism names or codes.
        
-
        +
         
 # until dplyr 1.0.0
 your_data %>% mutate_if(is.mic, as.rsi)
@@ -405,7 +456,7 @@
 
        • 
 
      • 
 
        Added intelligent data cleaning to as.disk(), so numbers can also be extracted from text and decimal numbers will always be rounded up:
        
-
        +
         
 as.disk(c("disk zone: 23.4 mm", 23.4))
 #> Class <disk>
@@ -459,14 +510,14 @@
 
        
 AMR 1.3.0 2020-07-31 
 
        
-
        
+
        
 
        
-New
        
+New
 
          
 
        • Function ab_from_text() to retrieve antimicrobial drug names, doses and forms of administration from clinical texts in e.g. health care records, which also corrects for misspelling since it uses as.ab() internally
          • 
 
        • 
 
          Tidyverse selection helpers for antibiotic classes, that help to select the columns of antibiotics that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations. They can be used in any function that allows selection helpers, like dplyr::select() and tidyr::pivot_longer():
          
-
          +
           
 library(dplyr)
 
@@ -483,9 +534,9 @@
 
        • Added argument conserve_capped_values to as.rsi() for interpreting MIC values - it makes sure that values starting with “<” (but not “<=”) will always return “S” and values starting with “>” (but not “>=”) will always return “R”. The default behaviour of as.rsi() has not changed, so you need to specifically do as.rsi(..., conserve_capped_values = TRUE).
          • 
 
        
 
        
-
        
+
        
 
        
-Changed
        
+Changed
 
 
        
-
        
+
        
 
        
-Changed
        
+Changed
 
          
 
        • Taxonomy:
 
            
@@ -606,17 +657,17 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
            
 AMR 1.1.0 2020-04-15 
 
            
-
            
+
            
 
            
-New
            
+New
 
              
 
            • Support for easy principal component analysis for AMR, using the new pca() function
              • 
 
            • Plotting biplots for principal component analysis using the new ggplot_pca() function
              • 
 
            
 
            
-
            
+
            
 
            
-Changed
            
+Changed
 
              
 
            • Improvements for the algorithm used by as.mo() (and consequently all mo_* functions, that use as.mo() internally):
 
                
@@ -648,14 +699,14 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                
 AMR 1.0.1 2020-02-23 
 
                
-
                
+
                
 
                
-Changed
                
+Changed
 
                  
 
                • Fixed important floating point error for some MIC comparisons in EUCAST 2020 guideline
                  • 
 
                • 
 
                  Interpretation from MIC values (and disk zones) to R/SI can now be used with mutate_at() of the dplyr package:
                  
-
                  +
                   
 yourdata %>% 
   mutate_at(vars(antibiotic1:antibiotic25), as.rsi, mo = "E. coli")
@@ -674,9 +725,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 AMR 1.0.0 2020-02-17 
 
 
                  This software is now out of beta and considered stable. Nonetheless, this package will be developed continually.
                  
-
                  
+
                  
 
                  
-New
                  
+New
 
                    
 
                  • Support for the newest EUCAST Clinical Breakpoint Tables v.10.0, valid from 1 January 2020. This affects translation of MIC and disk zones using as.rsi() and inferred resistance and susceptibility using eucast_rules().
                    • 
 
                  • The repository of this package now contains a clean version of the EUCAST and CLSI guidelines from 2011-2020 to translate MIC and disk diffusion values to R/SI: https://github.com/msberends/AMR/blob/master/data-raw/rsi_translation.txt. This allows for machine reading these guidelines, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI. This file used to process the EUCAST Clinical Breakpoints Excel file can be found here.
                    • 
@@ -684,7 +735,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                      
 
                    • 
 
                      Support for LOINC codes in the antibiotics data set. Use ab_loinc() to retrieve LOINC codes, or use a LOINC code for input in any ab_* function:
                      
-
                      +
                       
 ab_loinc("ampicillin")
 #> [1] "21066-6" "3355-5"  "33562-0" "33919-2" "43883-8" "43884-6" "87604-5"
@@ -695,7 +746,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                      • 
 
                    • 
 
                      Support for SNOMED CT codes in the microorganisms data set. Use mo_snomed() to retrieve SNOMED codes, or use a SNOMED code for input in any mo_* function:
                      
-
                      +
                       
 mo_snomed("S. aureus")
 #> [1] 115329001   3092008 113961008
@@ -760,11 +811,11 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                        
 
                      • 
 
                        If you were dependent on the old Enterobacteriaceae family e.g. by using in your code:
                        
-
                        +
                         
 if (mo_family(somebugs) == "Enterobacteriaceae") ...
                        
 
                        then please adjust this to:
                        
-
                        +
                         
 if (mo_order(somebugs) == "Enterobacterales") ...
                        
 
                        • 
@@ -772,13 +823,13 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
 
                      
 
                      
-
                      
+
                      
 
                      
-New
                      
+New
 
                        
 
                      • 
 
                        Functions susceptibility() and resistance() as aliases of proportion_SI() and proportion_R(), respectively. These functions were added to make it more clear that “I” should be considered susceptible and not resistant.
                        
-
                        +
                         
 library(dplyr)
 example_isolates %>%
@@ -807,7 +858,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                      • More intelligent way of coping with some consonants like “l” and “r”
                        • 
 
                      • 
 
                        Added a score (a certainty percentage) to mo_uncertainties(), that is calculated using the Levenshtein distance:
                        
-
                        +
                         
 as.mo(c("Stafylococcus aureus",
         "staphylokok aureuz"))
@@ -866,14 +917,14 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                          
 
                        • 
 
                          Determination of first isolates now excludes all ‘unknown’ microorganisms at default, i.e. microbial code "UNKNOWN". They can be included with the new argument include_unknown:
                          
-
                          +
                           
 first_isolate(..., include_unknown = TRUE)
                          
 
                          For WHONET users, this means that all records/isolates with organism code "con" (contamination) will be excluded at default, since as.mo("con") = "UNKNOWN". The function always shows a note with the number of ‘unknown’ microorganisms that were included or excluded.
                          
 
                          • 
 
                        • 
 
                          For code consistency, classes ab and mo will now be preserved in any subsetting or assignment. For the sake of data integrity, this means that invalid assignments will now result in NA:
                          
-
                          +
                           
 # how it works in base R:
 x <- factor("A")
@@ -892,13 +943,13 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                        • Renamed data set septic_patients to example_isolates
                          • 
 
                        
 
                        
-
                        
+
                        
 
                        
-New
                        
+New
 
                          
 
                        • 
 
                          Function bug_drug_combinations() to quickly get a data.frame with the results of all bug-drug combinations in a data set. The column containing microorganism codes is guessed automatically and its input is transformed with mo_shortname() at default:
                          
-
                          +
                           
 x <- bug_drug_combinations(example_isolates)
 #> NOTE: Using column `mo` as input for `col_mo`.
@@ -921,13 +972,13 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 #> 4 Gram-negative AMX 227  0 405   632
 #> NOTE: Use 'format()' on this result to get a publicable/printable format.
                          
 
                          You can format this to a printable format, ready for reporting or exporting to e.g. Excel with the base R format() function:
                          
-
                          +
                           
 format(x, combine_IR = FALSE)
                          
 
                          • 
 
                        • 
 
                          Additional way to calculate co-resistance, i.e. when using multiple antimicrobials as input for portion_* functions or count_* functions. This can be used to determine the empiric susceptibility of a combination therapy. A new argument only_all_tested (which defaults to FALSE) replaces the old also_single_tested and can be used to select one of the two methods to count isolates and calculate portions. The difference can be seen in this example table (which is also on the portion and count help pages), where the %SI is being determined:
                          
-
                          +
                           
 # --------------------------------------------------------------------
 #                     only_all_tested = FALSE  only_all_tested = TRUE
@@ -949,7 +1000,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                          • 
 
                        • 
 
                          tibble printing support for classes rsi, mic, disk, ab mo. When using tibbles containing antimicrobial columns, values S will print in green, values I will print in yellow and values R will print in red. Microbial IDs (class mo) will emphasise on the genus and species, not on the kingdom.
                          
-
                          +
                           
 # (run this on your own console, as this page does not support colour printing)
 library(dplyr)
@@ -959,9 +1010,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                          • 
 
                        
 
                        
-
                        
+
                        
 
                        
-Changed
                        
+Changed
 
                          
 
                        • Many algorithm improvements for as.mo() (of which some led to additions to the microorganisms data set). Many thanks to all contributors that helped improving the algorithms.
 
                            
@@ -1026,13 +1077,13 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                            
 AMR 0.7.1 2019-06-23 
 
                            
-
                            
+
                            
 
                            
-New
                            
+New
 
                              
 
                            • 
 
                              Function rsi_df() to transform a data.frame to a data set containing only the microbial interpretation (S, I, R), the antibiotic, the percentage of S/I/R and the number of available isolates. This is a convenient combination of the existing functions count_df() and portion_df() to immediately show resistance percentages and number of available isolates:
                              
-
                              +
                               
 septic_patients %>%
   select(AMX, CIP) %>%
@@ -1059,7 +1110,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                            • UPEC (Uropathogenic E. coli)
                              • 
 
                            
 
                            All these lead to the microbial ID of E. coli:
                            
-
                            +
                             
 as.mo("UPEC")
 # B_ESCHR_COL
@@ -1072,9 +1123,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                          • Function mo_synonyms() to get all previously accepted taxonomic names of a microorganism
                            • 
 
                          
 
                        
-
                        
+
                        
 
                        
-Changed
                        
+Changed
 
                          
 
                        • Column names of output count_df() and portion_df() are now lowercase
                          • 
 
                        • Fixed bug in translation of microorganism names
                          • 
@@ -1111,9 +1162,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                          
 AMR 0.7.0 2019-06-03 
 
                          
-
                          
+
                          
 
                          
-New
                          
+New
 
                            
 
                          • Support for translation of disk diffusion and MIC values to RSI values (i.e. antimicrobial interpretations). Supported guidelines are EUCAST (2011 to 2019) and CLSI (2011 to 2019). Use as.rsi() on an MIC value (created with as.mic()), a disk diffusion value (created with the new as.disk()) or on a complete date set containing columns with MIC or disk diffusion values.
                            • 
 
                          • Function mo_name() as alias of mo_fullname()
@@ -1121,9 +1172,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                          • Added guidelines of the WHO to determine multi-drug resistance (MDR) for TB (mdr_tb()) and added a new vignette about MDR. Read this tutorial here on our website.
                            • 
 
                          
 
                          
-
                          
+
                          
 
                          
-Changed
                          
+Changed
 
                            
 
                          • Fixed a critical bug in first_isolate() where missing species would lead to incorrect FALSEs. This bug was not present in AMR v0.5.0, but was in v0.6.0 and v0.6.1.
                            • 
 
                          • Fixed a bug in eucast_rules() where antibiotics from WHONET software would not be recognised
                            • 
@@ -1164,7 +1215,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                          • when all values are unique it now shows a message instead of a warning
                            • 
 
                          • 
 
                            support for boxplots:
                            
-
                            +
                             
 septic_patients %>% 
   freq(age) %>% 
@@ -1208,9 +1259,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                            
 AMR 0.6.1 2019-03-29 
 
                            
-
                            
+
                            
 
                            
-Changed
                            
+Changed
 
                              
 
                            • Fixed a critical bug when using eucast_rules() with verbose = TRUE
 
                              • 
@@ -1228,9 +1279,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                            • Contains the complete manual of this package and all of its functions with an explanation of their arguments
                              • 
 
                            • Contains a comprehensive tutorial about how to conduct antimicrobial resistance analysis, import data from WHONET or SPSS and many more.
                              • 
 
                            
-
                            
+
                            
 
                            
-New
                            
+New
 
                              
 
                            • BREAKING: removed deprecated functions, arguments and references to ‘bactid’. Use as.mo() to identify an MO code.
                              • 
 
                            • 
@@ -1259,7 +1310,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                              • 
 
                            • 
 
                              New filters for antimicrobial classes. Use these functions to filter isolates on results in one of more antibiotics from a specific class:
                              
-
                              +
                               
 filter_aminoglycosides()
 filter_carbapenems()
@@ -1273,7 +1324,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 filter_macrolides()
 filter_tetracyclines()
                              
 
                              The antibiotics data set will be searched, after which the input data will be checked for column names with a value in any abbreviations, codes or official names found in the antibiotics data set. For example:
                              
-
                              +
                               
 septic_patients %>% filter_glycopeptides(result = "R")
 # Filtering on glycopeptide antibacterials: any of `vanc` or `teic` is R
@@ -1282,7 +1333,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                              • 
 
                            • 
 
                              All ab_* functions are deprecated and replaced by atc_* functions:
                              
-
                              +
                               
 ab_property -> atc_property()
 ab_name -> atc_name()
@@ -1303,7 +1354,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                            • New function age_groups() to split ages into custom or predefined groups (like children or elderly). This allows for easier demographic antimicrobial resistance analysis per age group.
                              • 
 
                            • 
 
                              New function ggplot_rsi_predict() as well as the base R plot() function can now be used for resistance prediction calculated with resistance_predict():
                              
-
                              +
                               
 x <- resistance_predict(septic_patients, col_ab = "amox")
 plot(x)
@@ -1311,13 +1362,13 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                              • 
 
                            • 
 
                              Functions filter_first_isolate() and filter_first_weighted_isolate() to shorten and fasten filtering on data sets with antimicrobial results, e.g.:
                              
-
                              +
                               
 septic_patients %>% filter_first_isolate(...)
 # or
 filter_first_isolate(septic_patients, ...)
                              
 
                              is equal to:
                              
-
                              +
                               
 septic_patients %>%
   mutate(only_firsts = first_isolate(septic_patients, ...)) %>%
@@ -1328,9 +1379,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                            • New vignettes about how to conduct AMR analysis, predict antimicrobial resistance, use the G-test and more. These are also available (and even easier readable) on our website: https://msberends.gitlab.io/AMR.
                              • 
 
                            
 
                            
-
                            
+
                            
 
                            
-Changed
                            
+Changed
 
                              
 
                            • Function eucast_rules():
 
                                
@@ -1350,7 +1401,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                                  
 
                                • 
 
                                  Now handles incorrect spelling, like i instead of y and f instead of ph:
                                  
-
                                  +
                                   
 # mo_fullname() uses as.mo() internally
 
@@ -1362,7 +1413,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                                  • 
 
                                • 
 
                                  Uncertainty of the algorithm is now divided into four levels, 0 to 3, where the default allow_uncertain = TRUE is equal to uncertainty level 2. Run ?as.mo for more info about these levels.
                                  
-
                                  +
                                   
 # equal:
 as.mo(..., allow_uncertain = TRUE)
@@ -1377,7 +1428,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                                • All microbial IDs that found are now saved to a local file ~/.Rhistory_mo. Use the new function clean_mo_history() to delete this file, which resets the algorithms.
                                  • 
 
                                • 
 
                                  Incoercible results will now be considered ‘unknown’, MO code UNKNOWN. On foreign systems, properties of these will be translated to all languages already previously supported: German, Dutch, French, Italian, Spanish and Portuguese:
                                  
-
                                  +
                                   
 mo_genus("qwerty", language = "es")
 # Warning: 
@@ -1427,7 +1478,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                                    
 
                                  • 
 
                                    Support for tidyverse quasiquotation! Now you can create frequency tables of function outcomes:
                                    
-
                                    +
                                     
 # Determine genus of microorganisms (mo) in `septic_patients` data set:
 # OLD WAY
@@ -1474,9 +1525,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                                    
 AMR 0.5.0 2018-11-30 
 
                                    
-
                                    
+
                                    
 
                                    
-New
                                    
+New
 
                                      
 
                                    • Repository moved to GitLab
                                      • 
 
                                    • Function count_all to get all available isolates (that like all portion_* and count_* functions also supports summarise and group_by), the old n_rsi is now an alias of count_all
@@ -1487,9 +1538,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                                    • Functions mo_authors and mo_year to get specific values about the scientific reference of a taxonomic entry
                                      • 
 
                                    
 
                                    
-
                                    
+
                                    
 
                                    
-Changed
                                    
+Changed
 
                                      
 
                                    • Functions MDRO, BRMO, MRGN and EUCAST_exceptional_phenotypes were renamed to mdro, brmo, mrgn and eucast_exceptional_phenotypes
                                      • 
 
                                    • EUCAST_rules was renamed to eucast_rules, the old function still exists as a deprecated function
                                      • 
@@ -1511,7 +1562,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                                    • Fewer than 3 characters as input for as.mo will return NA
                                      • 
 
                                    • 
 
                                      Function as.mo (and all mo_* wrappers) now supports genus abbreviations with “species” attached
                                      
-
                                      +
                                       
 as.mo("E. species")        # B_ESCHR
 mo_fullname("E. spp.")     # "Escherichia species"
@@ -1528,7 +1579,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                                        
 
                                      • 
 
                                        Support for grouping variables, test with:
                                        
-
                                        +
                                         
 septic_patients %>% 
   group_by(hospital_id) %>% 
@@ -1536,7 +1587,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                                        • 
 
                                      • 
 
                                        Support for (un)selecting columns:
                                        
-
                                        +
                                         
 septic_patients %>% 
   freq(hospital_id) %>% 
@@ -1598,9 +1649,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                                        
 AMR 0.4.0 2018-10-01 
 
                                        
-
                                        
+
                                        
 
                                        
-New
                                        
+New
 
                                          
 
                                        • The data set microorganisms now contains all microbial taxonomic data from ITIS (kingdoms Bacteria, Fungi and Protozoa), the Integrated Taxonomy Information System, available via https://itis.gov. The data set now contains more than 18,000 microorganisms with all known bacteria, fungi and protozoa according ITIS with genus, species, subspecies, family, order, class, phylum and subkingdom. The new data set microorganisms.old contains all previously known taxonomic names from those kingdoms.
                                          • 
 
                                        • 
@@ -1616,7 +1667,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                                          • 
 
                                        
 
                                        They also come with support for German, Dutch, French, Italian, Spanish and Portuguese:
                                        
-
                                        +
                                         
 mo_gramstain("E. coli")
 # [1] "Gram negative"
@@ -1627,7 +1678,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 mo_fullname("S. group A", language = "pt") # Portuguese
 # [1] "Streptococcus grupo A"
                                        
 
                                        Furthermore, former taxonomic names will give a note about the current taxonomic name:
                                        
-
                                        +
                                         
 mo_gramstain("Esc blattae")
 # Note: 'Escherichia blattae' (Burgess et al., 1973) was renamed 'Shimwellia blattae' (Priest and Barker, 2010)
@@ -1642,7 +1693,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                                      • Function is.rsi.eligible to check for columns that have valid antimicrobial results, but do not have the rsi class yet. Transform the columns of your raw data with: data %>% mutate_if(is.rsi.eligible, as.rsi)
                                        • 
 
                                      • 
 
                                        Functions as.mo and is.mo as replacements for as.bactid and is.bactid (since the microoganisms data set not only contains bacteria). These last two functions are deprecated and will be removed in a future release. The as.mo function determines microbial IDs using intelligent rules:
                                        
-
                                        +
                                         
 as.mo("E. coli")
 # [1] B_ESCHR_COL
@@ -1651,7 +1702,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 as.mo("S group A")
 # [1] B_STRPTC_GRA
                                        
 
                                        And with great speed too - on a quite regular Linux server from 2007 it takes us less than 0.02 seconds to transform 25,000 items:
                                        
-
                                        +
                                         
 thousands_of_E_colis <- rep("E. coli", 25000)
 microbenchmark::microbenchmark(as.mo(thousands_of_E_colis), unit = "s")
@@ -1678,14 +1729,14 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                                      • Renamed septic_patients$sex to septic_patients$gender
                                        • 
 
                                      
 
                                      
-
                                      
+
                                      
 
                                      
-Changed
                                      
+Changed
 
                                        
 
                                      • Added three antimicrobial agents to the antibiotics data set: Terbinafine (D01BA02), Rifaximin (A07AA11) and Isoconazole (D01AC05)
                                        • 
 
                                      • 
 
                                        Added 163 trade names to the antibiotics data set, it now contains 298 different trade names in total, e.g.:
                                        
-
                                        +
                                         
 ab_official("Bactroban")
 # [1] "Mupirocin"
@@ -1702,7 +1753,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                                      • Added arguments minimum and as_percent to portion_df
                                        • 
 
                                      • 
 
                                        Support for quasiquotation in the functions series count_* and portions_*, and n_rsi. This allows to check for more than 2 vectors or columns.
                                        
-
                                        +
                                         
 septic_patients %>% select(amox, cipr) %>% count_IR()
 # which is the same as:
@@ -1722,12 +1773,12 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                                      • Added longest en shortest character length in the frequency table (freq) header of class character
                                        • 
 
                                      • 
 
                                        Support for types (classes) list and matrix for freq
                                        
-
                                        +
                                         
 my_matrix = with(septic_patients, matrix(c(age, gender), ncol = 2))
 freq(my_matrix)
                                        
 
                                        For lists, subsetting is possible:
                                        
-
                                        +
                                         
 my_list = list(age = septic_patients$age, gender = septic_patients$gender)
 my_list %>% freq(age)
@@ -1747,9 +1798,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                                        
 AMR 0.3.0 2018-08-14 
 
                                        
-
                                        
+
                                        
 
                                        
-New
                                        
+New
 
                                          
 
                                        • 
 BREAKING: rsi_df was removed in favour of new functions portion_R, portion_IR, portion_I, portion_SI and portion_S to selectively calculate resistance or susceptibility. These functions are 20 to 30 times faster than the old rsi function. The old function still works, but is deprecated.
@@ -1820,9 +1871,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                                          • 
 
                                        
 
                                        
-
                                        
+
                                        
 
                                        
-Changed
                                        
+Changed
 
                                          
 
                                        • Improvements for forecasting with resistance_predict and added more examples
                                          • 
 
                                        • More antibiotics added as arguments for EUCAST rules
                                          • 
@@ -1884,9 +1935,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                                          
 AMR 0.2.0 2018-05-03 
 
                                          
-
                                          
+
                                          
 
                                          
-New
                                          
+New
 
                                            
 
                                          • Full support for Windows, Linux and macOS
                                            • 
 
                                          • Full support for old R versions, only R-3.0.0 (April 2013) or later is needed (needed packages may have other dependencies)
                                            • 
@@ -1906,9 +1957,9 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                                          • New print format for tibbles and data.tables
                                            • 
 
                                          
 
                                          
-
                                          
+
                                          
 
                                          
-Changed
                                          
+Changed
 
                                            
 
                                          • Fixed rsi class for vectors that contain only invalid antimicrobial interpretations
                                            • 
 
                                          • Renamed dataset ablist to antibiotics
diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
index 3d893184..da1bab7c 100644
--- a/docs/pkgdown.yml
+++ b/docs/pkgdown.yml
@@ -12,7 +12,7 @@ articles:
   datasets: datasets.html
   resistance_predict: resistance_predict.html
   welcome_to_AMR: welcome_to_AMR.html
-last_built: 2021-01-05T08:44Z
+last_built: 2021-01-12T21:06Z
 urls:
   reference: https://msberends.github.io/AMR//reference
   article: https://msberends.github.io/AMR//articles
diff --git a/docs/reference/Rplot001.png b/docs/reference/Rplot001.png
new file mode 100644
index 00000000..17a35806
Binary files /dev/null and b/docs/reference/Rplot001.png differ
diff --git a/docs/reference/ab_from_text.html b/docs/reference/ab_from_text.html
index 92c2e880..f9a7e8be 100644
--- a/docs/reference/ab_from_text.html
+++ b/docs/reference/ab_from_text.html
@@ -82,7 +82,7 @@
       
       
         AMR (for R)
-        1.4.0.9053
+        1.5.0
       
     
                                          
 
diff --git a/docs/reference/antibiotic_class_selectors.html b/docs/reference/antibiotic_class_selectors.html
index 5d1d7186..c47ad251 100644
--- a/docs/reference/antibiotic_class_selectors.html
+++ b/docs/reference/antibiotic_class_selectors.html
@@ -82,7 +82,7 @@
       
       
         AMR (for R)
-        1.5.0
+        1.5.0.9000
       
     
                                          
 
diff --git a/docs/reference/antibiotics.html b/docs/reference/antibiotics.html
index 6c60e9e8..52154db6 100644
--- a/docs/reference/antibiotics.html
+++ b/docs/reference/antibiotics.html
@@ -6,7 +6,7 @@
 
 
 
-Data sets with 557 antimicrobials — antibiotics • AMR (for R)
+Data sets with 558 antimicrobials — antibiotics • AMR (for R)
 
 
 
@@ -48,7 +48,7 @@
   
   
 
-
+
 
 
 
@@ -233,7 +233,7 @@
 
                                          
   
                                          
     
                                          
-    
                                          Data sets with 557 antimicrobials
                                          
+    
                                          Data sets with 558 antimicrobials
                                          
     Source: R/data.R
     
     
                                          
@@ -250,7 +250,7 @@
     
                                          Format
                                          
 
     
-
                                          For the antibiotics data set: a data.frame with 455 observations and 14 variables:
                                          
+
                                          For the antibiotics data set: a data.frame with 456 observations and 14 variables:
                                          
 
 
                                            
 
                                          • ab
                                             Antibiotic ID as used in this package (such as AMC), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available
                                            • 
diff --git a/docs/reference/as.mo.html b/docs/reference/as.mo.html
index 01b5a0ad..47539e07 100644
--- a/docs/reference/as.mo.html
+++ b/docs/reference/as.mo.html
@@ -82,7 +82,7 @@
       
       
         AMR (for R)
-        1.5.0
+        1.5.0.9000
       
     
                                          
 
@@ -387,14 +387,14 @@ The lifecycle of this function is stableWith ambiguous user input in as.mo() and all the mo_* functions, the returned results are chosen based on their matching score using mo_matching_score(). This matching score \(m\), is calculated as:
                                          
-
                                          $$m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \textrm{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}$$
                                          
+
                                          mo matching score
                                          
 
                                          where:
                                            
-
                                          • \(x\) is the user input;
                                            • 
-
                                          • \(n\) is a taxonomic name (genus, species, and subspecies);
                                            • 
-
                                          • \(l_n\) is the length of \(n\);
                                            • 
-
                                          • lev is the Levenshtein distance function, which counts any insertion, deletion and substitution as 1 that is needed to change \(x\) into \(n\);
                                            • 
-
                                          • \(p_n\) is the human pathogenic prevalence group of \(n\), as described below;
                                            • 
-
                                          • \(k_n\) is the taxonomic kingdom of \(n\), set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.
                                            • 
+
                                          • x is the user input;
                                            • 
+
                                          • n is a taxonomic name (genus, species, and subspecies);
                                            • 
+
                                          • ln is the length of n;
                                            • 
+
                                          • lev is the Levenshtein distance function, which counts any insertion, deletion and substitution as 1 that is needed to change x into n;
                                            • 
+
                                          • pn is the human pathogenic prevalence group of n, as described below;
                                            • 
+
                                          • kn is the taxonomic kingdom of n, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.
                                            • 
 
                                          
 
 
                                          The grouping into human pathogenic prevalence (\(p\)) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. Group 1 (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is Enterococcus, Staphylococcus or Streptococcus. This group consequently contains all common Gram-negative bacteria, such as Pseudomonas and Legionella and all species within the order Enterobacterales. Group 2 consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is Absidia, Acremonium, Actinotignum, Alternaria, Anaerosalibacter, Apophysomyces, Arachnia, Aspergillus, Aureobacterium, Aureobasidium, Bacteroides, Basidiobolus, Beauveria, Blastocystis, Branhamella, Calymmatobacterium, Candida, Capnocytophaga, Catabacter, Chaetomium, Chryseobacterium, Chryseomonas, Chrysonilia, Cladophialophora, Cladosporium, Conidiobolus, Cryptococcus, Curvularia, Exophiala, Exserohilum, Flavobacterium, Fonsecaea, Fusarium, Fusobacterium, Hendersonula, Hypomyces, Koserella, Lelliottia, Leptosphaeria, Leptotrichia, Malassezia, Malbranchea, Mortierella, Mucor, Mycocentrospora, Mycoplasma, Nectria, Ochroconis, Oidiodendron, Phoma, Piedraia, Pithomyces, Pityrosporum, Prevotella,\Pseudallescheria, Rhizomucor, Rhizopus, Rhodotorula, Scolecobasidium, Scopulariopsis, Scytalidium,Sporobolomyces, Stachybotrys, Stomatococcus, Treponema, Trichoderma, Trichophyton, Trichosporon, Tritirachium or Ureaplasma. Group 3 consists of all other microorganisms.
                                          
diff --git a/docs/reference/as.rsi.html b/docs/reference/as.rsi.html
index c678db22..2cb44f93 100644
--- a/docs/reference/as.rsi.html
+++ b/docs/reference/as.rsi.html
@@ -322,7 +322,7 @@
     
     
       add_intrinsic_resistance
-      
                                          (only useful when using a EUCAST guideline) a logical to indicate whether intrinsic antibiotic resistance must also be considered for applicable bug-drug combinations, meaning that e.g. ampicillin will always return "R" in Klebsiella species. Determination is based on the intrinsic_resistant data set, that itself is based on 'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2 from 2020.
                                          
+      
                                          (only useful when using a EUCAST guideline) a logical to indicate whether intrinsic antibiotic resistance must also be considered for applicable bug-drug combinations, meaning that e.g. ampicillin will always return "R" in Klebsiella species. Determination is based on the intrinsic_resistant data set, that itself is based on 'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2 (2020).
                                          
     
     
       reference_data
diff --git a/docs/reference/catalogue_of_life.html b/docs/reference/catalogue_of_life.html
index e081c25b..bdd83f93 100644
--- a/docs/reference/catalogue_of_life.html
+++ b/docs/reference/catalogue_of_life.html
@@ -82,7 +82,7 @@
       
       
         AMR (for R)
-        1.5.0
+        1.5.0.9000
       
     
                                          
 
diff --git a/docs/reference/catalogue_of_life_version.html b/docs/reference/catalogue_of_life_version.html
index 7bd4026b..511daba6 100644
--- a/docs/reference/catalogue_of_life_version.html
+++ b/docs/reference/catalogue_of_life_version.html
@@ -82,7 +82,7 @@
       
       
         AMR (for R)
-        1.5.0
+        1.5.0.9000
       
     
                                          
 
diff --git a/docs/reference/dosage.html b/docs/reference/dosage.html
new file mode 100644
index 00000000..c5dcdd60
--- /dev/null
+++ b/docs/reference/dosage.html
@@ -0,0 +1,303 @@
+
+
+
+  
+  
+
+
+
+Data set with treatment dosages as defined by EUCAST — dosage • AMR (for R)
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+  
+  
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+  
+
+  
+    
                                          
+      
                                          
+      
+
+      
+
+      
                                          
+
+
                                          
+  
                                          
+    
                                          
+    
                                          Data set with treatment dosages as defined by EUCAST
                                          
+    Source: R/data.R
+    
+    
                                          
+
+    
                                          
+    
                                          EUCAST breakpoints used in this package are based on the dosages in this data set. They can be retrieved with eucast_dosage().
                                          
+    
                                          
+
+    
                                          dosage
                                          
+
+
+    
                                          Format
                                          
+
+    
                                          A data.frame with 135 observations and 9 variables:
                                            
+
                                          • ab
                                             Antibiotic ID as used in this package (such as AMC), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available
                                            • 
+
                                          • name
                                             Official name of the antimicrobial agent as used by WHONET/EARS-Net or the WHO
                                            • 
+
                                          • type
                                             Type of the dosage, either "high_dosage", "standard_dosage" or "uncomplicated_uti"
                                            • 
+
                                          • dose
                                             Dose, such as "2 g" or "25 mg/kg"
                                            • 
+
                                          • dose_times
                                             Dose, such as "2 g" or "25 mg/kg"
                                            • 
+
                                          • administration
                                             Route of administration, either "im", "iv" or "oral"
                                            • 
+
                                          • notes
                                             Additional dosage notes
                                            • 
+
                                          • original_txt
                                             Original text in the PDF file of EUCAST
                                            • 
+
                                          • eucast_version
                                             Version number of the EUCAST Clinical Breakpoints guideline to which these dosages apply
                                            • 
+
                                          
+
+    
                                          Details
                                          
+
+    
                                          'EUCAST Clinical Breakpoint Tables' v11.0 (2021) are based on the dosages in this data set.
                                          
+    
                                          Reference data publicly available
                                          
+
+    
+
+
                                          All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this AMR package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find all download links on our website, which is automatically updated with every code change.
                                          
+    
                                          Read more on our website!
                                          
+
+    
+
+
                                          On our website https://msberends.github.io/AMR/ you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions and an example analysis using WHONET data. As we would like to better understand the backgrounds and needs of our users, please participate in our survey!
                                          
+
+  
                                          
+  
+
                                          
+
+
+      
+   
                                          
+
+  
+
+
+  
+
+
+
diff --git a/docs/reference/eucast_rules.html b/docs/reference/eucast_rules.html
index aaffd41c..65de1adf 100644
--- a/docs/reference/eucast_rules.html
+++ b/docs/reference/eucast_rules.html
@@ -49,7 +49,7 @@
   
 
 
-
 
 
@@ -240,7 +240,7 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied
     
                                        
 
     
                                        
-    
                                        Apply rules for clinical breakpoints and intrinsic resistance as defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST, https://eucast.org), see Source.
                                        
+    
                                        Apply rules for clinical breakpoints and intrinsic resistance as defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST, https://eucast.org), see Source. Use eucast_dosage() to get advised dosages of a certain bug-drug combination, which is based on the dosage data set.
                                        
 
                                        To improve the interpretation of the antibiogram before EUCAST rules are applied, some non-EUCAST rules can applied at default, see Details.
                                        
     
                                        
 
@@ -254,7 +254,9 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied
   version_expertrules = 3.2,
   ampc_cephalosporin_resistance = NA,
   ...
-)
                                        
+)
+
+eucast_dosage(ab, administration = "iv", version_breakpoints = 11)
                                        
 
     
                                        Arguments
                                        
     
@@ -281,7 +283,7 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied
     
-      
+      
@@ -295,6 +297,14 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied
       
+    
+      
+      
+    
+    
+      
+      
+    
                                        
     
                                        
       version_breakpoints
                                        the version number to use for the EUCAST Clinical Breakpoints guideline. Currently supported: 10.0.
                                        the version number to use for the EUCAST Clinical Breakpoints guideline. Currently supported: 11.0, 10.0.
                                        		
     
                                        
     
                                        
       version_expertrules...
       
                                        column name of an antibiotic, please see section Antibiotics below
                                        		
     
                                        ab
                                        any (vector of) text that can be coerced to a valid antibiotic code with as.ab()
                                        administration
                                        route of administration, either "im", "iv" or "oral"
                                        
     
                                        
 
     
                                        Source
                                        
@@ -307,6 +317,7 @@ Leclercq et al. EUCAST expert rules in antimicrobial susceptibility test
 
                                      • EUCAST Intrinsic Resistance and Unusual Phenotypes. Version 3.2, 2020. (link)
                                        • 
 
                                      • EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 9.0, 2019. (link)
                                        • 
 
                                      • EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 10.0, 2020. (link)
                                        • 
+
                                      • EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 11.0, 2021. (link)
                                        • 
 
                                      
 
     
                                      Value
                                      
@@ -393,6 +404,8 @@ The lifecycle of this function is stable# containing all details about the transformations:
 c <- eucast_rules(a, verbose = TRUE)
 # }
+
+eucast_dosage(c("tobra", "genta", "cipro"), "iv")
 
                                      
   
                                      
   
                                    
diff --git a/docs/reference/first_isolate.html b/docs/reference/first_isolate.html
index f66c3d98..77363e34 100644
--- a/docs/reference/first_isolate.html
+++ b/docs/reference/first_isolate.html
@@ -285,7 +285,7 @@
     
     
       x
-      
                                    a data.frame containing isolates. Can be left blank when used inside dplyr verbs, such as filter(), mutate() and summarise().
                                    
+      
                                    a data.frame containing isolates. Can be left blank for automatic determination.
                                    
     
     
       col_date
diff --git a/docs/reference/index.html b/docs/reference/index.html
index 36aa3ff6..9d27a35c 100644
--- a/docs/reference/index.html
+++ b/docs/reference/index.html
@@ -81,7 +81,7 @@
       
       
         AMR (for R)
-        1.5.0
+        1.5.0.9000
       
     
                                    
 
@@ -263,6 +263,48 @@
         
                                    The AMR Package
                                    
       
         
+        
+          
                                    example_isolates 
                                    
+        
+        
                                    Data set with 2,000 example isolates
                                    
+      
+        
+        
+          
                                    microorganisms 
                                    
+        
+        
                                    Data set with 67,151 microorganisms
                                    
+      
+        
+        
+          
                                    microorganisms.codes 
                                    
+        
+        
                                    Data set with 5,580 common microorganism codes
                                    
+      
+        
+        
+          
                                    microorganisms.old 
                                    
+        
+        
                                    Data set with previously accepted taxonomic names
                                    
+      
+        
+        
+          
                                    antibiotics antivirals 
                                    
+        
+        
                                    Data sets with 558 antimicrobials
                                    
+      
+        
+        
+          
                                    intrinsic_resistant 
                                    
+        
+        
                                    Data set with bacterial intrinsic resistance
                                    
+      
+        
+        
+          
                                    dosage 
                                    
+        
+        
                                    Data set with treatment dosages as defined by EUCAST
                                    
+      
+        
         
           
                                    catalogue_of_life 
                                    
         
@@ -287,30 +329,6 @@
         
                                    Lifecycles of functions in the AMR package
                                    
       
         
-        
-          
                                    microorganisms 
                                    
-        
-        
                                    Data set with 67,151 microorganisms
                                    
-      
-        
-        
-          
                                    antibiotics antivirals 
                                    
-        
-        
                                    Data sets with 557 antimicrobials
                                    
-      
-        
-        
-          
                                    intrinsic_resistant 
                                    
-        
-        
                                    Data set with bacterial intrinsic resistance
                                    
-      
-        
-        
-          
                                    example_isolates 
                                    
-        
-        
                                    Data set with 2,000 example isolates
                                    
-      
-        
         
           
                                    example_isolates_unclean 
                                    
         
@@ -323,18 +341,6 @@
         
                                    Data set for R/SI interpretation
                                    
       
         
-        
-          
                                    microorganisms.codes 
                                    
-        
-        
                                    Data set with 5,583 common microorganism codes
                                    
-      
-        
-        
-          
                                    microorganisms.old 
                                    
-        
-        
                                    Data set with previously accepted taxonomic names
                                    
-      
-        
         
           
                                    WHONET 
                                    
         
@@ -361,7 +367,7 @@
       
         
         
-          
                                    mo_name() mo_fullname() mo_shortname() mo_subspecies() mo_species() mo_genus() mo_family() mo_order() mo_class() mo_phylum() mo_kingdom() mo_domain() mo_type() mo_gramstain() mo_is_gram_negative() mo_is_gram_positive() mo_is_intrinsic_resistant() mo_snomed() mo_ref() mo_authors() mo_year() mo_rank() mo_taxonomy() mo_synonyms() mo_info() mo_url() mo_property() 
                                    
+          
                                    mo_name() mo_fullname() mo_shortname() mo_subspecies() mo_species() mo_genus() mo_family() mo_order() mo_class() mo_phylum() mo_kingdom() mo_domain() mo_type() mo_gramstain() mo_is_gram_negative() mo_is_gram_positive() mo_is_yeast() mo_is_intrinsic_resistant() mo_snomed() mo_ref() mo_authors() mo_year() mo_rank() mo_taxonomy() mo_synonyms() mo_info() mo_url() mo_property() 
                                    
         
         
                                    Get properties of a microorganism
                                    
       
@@ -441,7 +447,7 @@
       
         
         
-          
                                    eucast_rules() 
                                    
+          
                                    eucast_rules() eucast_dosage() 
                                    
         
         
                                    Apply EUCAST rules
                                    
       
@@ -450,6 +456,12 @@
           
                                    plot(<disk>) plot(<mic>) barplot(<mic>) plot(<rsi>) barplot(<rsi>) 
                                    
         
         
                                    Plotting for classes rsi, mic and disk
                                    
+      
+        
+        
+          
                                    isolate_identifier() 
                                    
+        
+        
                                    Create identifier of an isolate
                                    
       
     
       
diff --git a/docs/reference/intrinsic_resistant.html b/docs/reference/intrinsic_resistant.html
index 8e4efe2b..8ba2fc99 100644
--- a/docs/reference/intrinsic_resistant.html
+++ b/docs/reference/intrinsic_resistant.html
@@ -255,7 +255,7 @@
     
                                    Details
                                    
 
     
                                    The repository of this AMR package contains a file comprising this exact data set: https://github.com/msberends/AMR/blob/master/data-raw/intrinsic_resistant.txt. This file allows for machine reading EUCAST guidelines about intrinsic resistance, which is almost impossible with the Excel and PDF files distributed by EUCAST. The file is updated automatically.
                                    
-
                                    This data set is based on 'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2 from 2020.
                                    
+
                                    This data set is based on 'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2 (2020).
                                    
     
                                    Reference data publicly available
                                    
 
     
diff --git a/docs/reference/isolate_identifier.html b/docs/reference/isolate_identifier.html
new file mode 100644
index 00000000..7e090f47
--- /dev/null
+++ b/docs/reference/isolate_identifier.html
@@ -0,0 +1,313 @@
+
+
+
+  
+  
+
+
+
+Create identifier of an isolate — isolate_identifier • AMR (for R)
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+  
+  
+
+
+
+
+
+
+
+
+
+
+
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+
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+
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+  
+
+  
+    
                                    
+      
                                    
+      
+
+      
+
+      
                                    
+
+
                                    
+  
                                    
+    
                                    
+    
                                    Create identifier of an isolate
                                    
+    Source: R/isolate_identifier.R
+    
+    
                                    
+
+    
                                    
+    
                                    This function will paste the microorganism code with all antimicrobial results into one string for each row in a data set. This is useful to compare isolates, e.g. between institutions or regions, when there is no genotyping available.
                                    
+    
                                    
+
+    
                                    isolate_identifier(x, col_mo = NULL, cols_ab = NULL)
                                    
+
+    
                                    Arguments
                                    
+    
+    
+    
+      
+      
+    
+    
+      
+      
+    
+    
+      
+      
+    
+    
                                    x
                                    data with antibiotic columns, such as amox, AMX and AMC
                                    col_mo
                                    column name of the IDs of the microorganisms (see as.mo()), defaults to the first column of class mo. Values will be coerced using as.mo().
                                    cols_ab
                                    a character vector of column names of x, or (a combination with) an antibiotic selector function, such as carbapenems() and aminoglysides()
                                    
+
+    
                                    Maturing lifecycle
                                    
+
+    
+
+
                                     
                                    
+The lifecycle of this function is maturing. The unlying code of a maturing function has been roughed out, but finer details might still change. Since this function needs wider usage and more extensive testing, you are very welcome to suggest changes at our repository or write us an email (see section 'Contact Us').
                                    
+    
                                    Read more on our website!
                                    
+
+    
+
+
                                    On our website https://msberends.github.io/AMR/ you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions and an example analysis using WHONET data. As we would like to better understand the backgrounds and needs of our users, please participate in our survey!
                                    
+
+    
                                    Examples
                                    
+    
                                    # automatic selection of microorganism and antibiotics (i.e., all <rsi> columns, see ?as.rsi)
+x <- isolate_identifier(example_isolates)
+
+# ignore microorganism codes, only use antimicrobial results
+x <- isolate_identifier(example_isolates, col_mo = FALSE, cols_ab = c("AMX", "TZP", "GEN", "TOB"))
+
+# select antibiotics from certain antibiotic classes
+x <- isolate_identifier(example_isolates, cols_ab = c(carbapenems(), aminoglycosides()))
+
                                    
+  
                                    
+  
+
                                    
+
+
+      
+   
                                    
+
+  
+
+
+  
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+
+
diff --git a/docs/reference/mdro.html b/docs/reference/mdro.html
index 13ce229e..937e32e2 100644
--- a/docs/reference/mdro.html
+++ b/docs/reference/mdro.html
@@ -268,7 +268,7 @@
     
     
       x
-      
                                    a data.frame with antibiotics columns, like AMX or amox. Can be left blank when used inside dplyr verbs, such as filter(), mutate() and summarise().
                                    
+      
                                    a data.frame with antibiotics columns, like AMX or amox. Can be left blank for automatic determination.
                                    
     
     
       guideline
diff --git a/docs/reference/microorganisms.codes.html b/docs/reference/microorganisms.codes.html
index c65e00b4..8c61444f 100644
--- a/docs/reference/microorganisms.codes.html
+++ b/docs/reference/microorganisms.codes.html
@@ -6,7 +6,7 @@
 
 
 
-Data set with 5,583 common microorganism codes — microorganisms.codes • AMR (for R)
+Data set with 5,580 common microorganism codes — microorganisms.codes • AMR (for R)
 
 
 
@@ -48,7 +48,7 @@
   
   
 
-
+
 
 
 
@@ -233,7 +233,7 @@
 
                                    
   
                                    
     
                                    
-    
                                    Data set with 5,583 common microorganism codes
                                    
+    
                                    Data set with 5,580 common microorganism codes
                                    
     Source: R/data.R
     
     
                                    
@@ -247,7 +247,7 @@
 
     
                                    Format
                                    
 
-    
                                    A data.frame with 5,583 observations and 2 variables:
                                      
+    
                                      A data.frame with 5,580 observations and 2 variables:
                                        
 
                                      • code
                                         Commonly used code of a microorganism
                                        • 
 
                                      • mo
                                         ID of the microorganism in the microorganisms data set
                                        • 
 
                                      
diff --git a/docs/reference/microorganisms.html b/docs/reference/microorganisms.html
index f93acaf3..e49209ee 100644
--- a/docs/reference/microorganisms.html
+++ b/docs/reference/microorganisms.html
@@ -266,7 +266,11 @@
 
                                      Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures, Germany, Prokaryotic Nomenclature Up-to-Date, https://www.dsmz.de/services/online-tools/prokaryotic-nomenclature-up-to-date and https://lpsn.dsmz.de (check included version with catalogue_of_life_version()).
                                      
     
                                      Details
                                      
 
-    
                                      Manually added were:
                                        
+    
                                        Please note that entries are only based on the Catalogue of Life and the LPSN (see below). Since these sources incorporate entries based on (recent) publications in the International Journal of Systematic and Evolutionary Microbiology (IJSEM), it can happen that the year of publication is sometimes later than one might expect.
                                        
+
                                        For example, Staphylococcus pettenkoferi was newly named in Diagnostic Microbiology and Infectious Disease in 2002 (PMID 12106949), but it was not before 2007 that a publication in IJSEM followed (PMID 17625191). Consequently, the AMR package returns 2007 for mo_year("S. pettenkoferi").
                                        Manually additions
                                        
+
+
+
                                        For convenience, some entries were added manually:
                                          
 
                                        • 11 entries of Streptococcus (beta-haemolytic: groups A, B, C, D, F, G, H, K and unspecified; other: viridans, milleri)
                                          • 
 
                                        • 2 entries of Staphylococcus (coagulase-negative (CoNS) and coagulase-positive (CoPS))
                                          • 
 
                                        • 3 entries of Trichomonas (Trichomonas vaginalis, and its family and genus)
                                          • 
@@ -276,6 +280,8 @@
 
                                        • 6 families under the Enterobacterales order, according to Adeolu et al. (2016, PMID 27620848), that are not (yet) in the Catalogue of Life
                                          • 
 
                                        • 7,411 species from the DSMZ (Deutsche Sammlung von Mikroorganismen und Zellkulturen) since the DSMZ contain the latest taxonomic information based on recent publications
                                          • 
 
                                        
+
+
 
                                        Direct download
                                        
 
 
diff --git a/docs/reference/microorganisms.old.html b/docs/reference/microorganisms.old.html
index c8a65212..5f055bd1 100644
--- a/docs/reference/microorganisms.old.html
+++ b/docs/reference/microorganisms.old.html
@@ -82,7 +82,7 @@
       
       
         AMR (for R)
-        1.5.0
+        1.5.0.9000
       
     
                                    
 
diff --git a/docs/reference/mo_matching_score.html b/docs/reference/mo_matching_score.html
index 3cd1361d..12cfaa3d 100644
--- a/docs/reference/mo_matching_score.html
+++ b/docs/reference/mo_matching_score.html
@@ -82,7 +82,7 @@
       
       
         AMR (for R)
-        1.5.0
+        1.5.0.9000
       
     
                                    
 
@@ -262,14 +262,14 @@
     
 
 
                                    With ambiguous user input in as.mo() and all the mo_* functions, the returned results are chosen based on their matching score using mo_matching_score(). This matching score \(m\), is calculated as:
                                    
-
                                    $$m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \textrm{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}$$
                                    
+
                                    mo matching score
                                    
 
                                    where:
                                      
-
                                    • \(x\) is the user input;
                                      • 
-
                                    • \(n\) is a taxonomic name (genus, species, and subspecies);
                                      • 
-
                                    • \(l_n\) is the length of \(n\);
                                      • 
-
                                    • lev is the Levenshtein distance function, which counts any insertion, deletion and substitution as 1 that is needed to change \(x\) into \(n\);
                                      • 
-
                                    • \(p_n\) is the human pathogenic prevalence group of \(n\), as described below;
                                      • 
-
                                    • \(k_n\) is the taxonomic kingdom of \(n\), set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.
                                      • 
+
                                    • x is the user input;
                                      • 
+
                                    • n is a taxonomic name (genus, species, and subspecies);
                                      • 
+
                                    • ln is the length of n;
                                      • 
+
                                    • lev is the Levenshtein distance function, which counts any insertion, deletion and substitution as 1 that is needed to change x into n;
                                      • 
+
                                    • pn is the human pathogenic prevalence group of n, as described below;
                                      • 
+
                                    • kn is the taxonomic kingdom of n, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.
                                      • 
 
                                    
 
 
                                    The grouping into human pathogenic prevalence (\(p\)) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. Group 1 (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is Enterococcus, Staphylococcus or Streptococcus. This group consequently contains all common Gram-negative bacteria, such as Pseudomonas and Legionella and all species within the order Enterobacterales. Group 2 consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is Absidia, Acremonium, Actinotignum, Alternaria, Anaerosalibacter, Apophysomyces, Arachnia, Aspergillus, Aureobacterium, Aureobasidium, Bacteroides, Basidiobolus, Beauveria, Blastocystis, Branhamella, Calymmatobacterium, Candida, Capnocytophaga, Catabacter, Chaetomium, Chryseobacterium, Chryseomonas, Chrysonilia, Cladophialophora, Cladosporium, Conidiobolus, Cryptococcus, Curvularia, Exophiala, Exserohilum, Flavobacterium, Fonsecaea, Fusarium, Fusobacterium, Hendersonula, Hypomyces, Koserella, Lelliottia, Leptosphaeria, Leptotrichia, Malassezia, Malbranchea, Mortierella, Mucor, Mycocentrospora, Mycoplasma, Nectria, Ochroconis, Oidiodendron, Phoma, Piedraia, Pithomyces, Pityrosporum, Prevotella,\Pseudallescheria, Rhizomucor, Rhizopus, Rhodotorula, Scolecobasidium, Scopulariopsis, Scytalidium,Sporobolomyces, Stachybotrys, Stomatococcus, Treponema, Trichoderma, Trichophyton, Trichosporon, Tritirachium or Ureaplasma. Group 3 consists of all other microorganisms.
                                    
@@ -281,6 +281,16 @@
 
                                     
                                    
 The lifecycle of this function is stable. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
                                    
 
                                    If the unlying code needs breaking changes, they will occur gradually. For example, a argument will be deprecated and first continue to work, but will emit an message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
                                    
+    
                                    Reference data publicly available
                                    
+
+    
+
+
                                    All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this AMR package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find all download links on our website, which is automatically updated with every code change.
                                    
+    
                                    Read more on our website!
                                    
+
+    
+
+
                                    On our website https://msberends.github.io/AMR/ you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions and an example analysis using WHONET data. As we would like to better understand the backgrounds and needs of our users, please participate in our survey!
                                    
     
                                    Author
                                    
 
     
                                    Matthijs S. Berends
                                    
diff --git a/docs/reference/mo_property.html b/docs/reference/mo_property.html
index 37b8d5b6..c97c0ef1 100644
--- a/docs/reference/mo_property.html
+++ b/docs/reference/mo_property.html
@@ -82,7 +82,7 @@
       
       
         AMR (for R)
-        1.5.0
+        1.5.0.9000
       
     
                                    
 
@@ -274,6 +274,8 @@
 
 mo_is_gram_positive(x, language = get_locale(), ...)
 
+mo_is_yeast(x, language = get_locale(), ...)
+
 mo_is_intrinsic_resistant(x, ab, language = get_locale(), ...)
 
 mo_snomed(x, language = get_locale(), ...)
@@ -301,7 +303,7 @@
     
     
       x
-      
                                    any character (vector) that can be coerced to a valid microorganism code with as.mo(). Can be left blank for auto-guessing the column containing microorganism codes when used inside dplyr verbs, such as filter(), mutate() and summarise(), please see Examples.
                                    
+      
                                    any character (vector) that can be coerced to a valid microorganism code with as.mo(). Can be left blank for auto-guessing the column containing microorganism codes if used in a data set, please see Examples.
                                    
     
     
       language
@@ -347,7 +349,8 @@
 
                                    The short name - mo_shortname() - almost always returns the first character of the genus and the full species, like "E. coli". Exceptions are abbreviations of staphylococci (such as "CoNS", Coagulase-Negative Staphylococci) and beta-haemolytic streptococci (such as "GBS", Group B Streptococci). Please bear in mind that e.g. E. coli could mean Escherichia coli (kingdom of Bacteria) as well as Entamoeba coli (kingdom of Protozoa). Returning to the full name will be done using as.mo() internally, giving priority to bacteria and human pathogens, i.e. "E. coli" will be considered Escherichia coli. In other words, mo_fullname(mo_shortname("Entamoeba coli")) returns "Escherichia coli".
                                    
 
                                    Since the top-level of the taxonomy is sometimes referred to as 'kingdom' and sometimes as 'domain', the functions mo_kingdom() and mo_domain() return the exact same results.
                                    
 
                                    The Gram stain - mo_gramstain() - will be determined based on the taxonomic kingdom and phylum. According to Cavalier-Smith (2002, PMID 11837318), who defined subkingdoms Negibacteria and Posibacteria, only these phyla are Posibacteria: Actinobacteria, Chloroflexi, Firmicutes and Tenericutes. These bacteria are considered Gram-positive - all other bacteria are considered Gram-negative. Species outside the kingdom of Bacteria will return a value NA. Functions mo_is_gram_negative() and mo_is_gram_positive() always return TRUE or FALSE (except when the input is NA or the MO code is UNKNOWN), thus always return FALSE for species outside the taxonomic kingdom of Bacteria.
                                    
-
                                    Intrinsic resistance - mo_is_intrinsic_resistant() - will be determined based on the intrinsic_resistant data set, which is based on 'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2 from 2020. The mo_is_intrinsic_resistant() can be vectorised over arguments x (input for microorganisms) and over ab (input for antibiotics).
                                    
+
                                    Determination of yeasts - mo_is_yeast() - will be based on the taxonomic phylum, class and order. Budding yeasts are true fungi of the phylum Ascomycetes, class Saccharomycetes (also called Hemiascomycetes). The true yeasts are separated into one main order Saccharomycetales. For all microorganisms that are in one of those two groups, the function will return TRUE. It returns FALSE for all other taxonomic entries.
                                    
+
                                    Intrinsic resistance - mo_is_intrinsic_resistant() - will be determined based on the intrinsic_resistant data set, which is based on 'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2 (2020). The mo_is_intrinsic_resistant() can be vectorised over arguments x (input for microorganisms) and over ab (input for antibiotics).
                                    
 
                                    All output will be translated where possible.
                                    
 
                                    The function mo_url() will return the direct URL to the online database entry, which also shows the scientific reference of the concerned species.
                                    
     
                                    Stable lifecycle
                                    
@@ -362,14 +365,14 @@ The lifecycle of this function is stableWith ambiguous user input in as.mo() and all the mo_* functions, the returned results are chosen based on their matching score using mo_matching_score(). This matching score \(m\), is calculated as:
                                    
-
                                    $$m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \textrm{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}$$
                                    
+
                                    mo matching score
                                    
 
                                    where:
                                      
-
                                    • \(x\) is the user input;
                                      • 
-
                                    • \(n\) is a taxonomic name (genus, species, and subspecies);
                                      • 
-
                                    • \(l_n\) is the length of \(n\);
                                      • 
-
                                    • lev is the Levenshtein distance function, which counts any insertion, deletion and substitution as 1 that is needed to change \(x\) into \(n\);
                                      • 
-
                                    • \(p_n\) is the human pathogenic prevalence group of \(n\), as described below;
                                      • 
-
                                    • \(k_n\) is the taxonomic kingdom of \(n\), set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.
                                      • 
+
                                    • x is the user input;
                                      • 
+
                                    • n is a taxonomic name (genus, species, and subspecies);
                                      • 
+
                                    • ln is the length of n;
                                      • 
+
                                    • lev is the Levenshtein distance function, which counts any insertion, deletion and substitution as 1 that is needed to change x into n;
                                      • 
+
                                    • pn is the human pathogenic prevalence group of n, as described below;
                                      • 
+
                                    • kn is the taxonomic kingdom of n, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.
                                      • 
 
                                    
 
 
                                    The grouping into human pathogenic prevalence (\(p\)) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. Group 1 (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is Enterococcus, Staphylococcus or Streptococcus. This group consequently contains all common Gram-negative bacteria, such as Pseudomonas and Legionella and all species within the order Enterobacterales. Group 2 consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is Absidia, Acremonium, Actinotignum, Alternaria, Anaerosalibacter, Apophysomyces, Arachnia, Aspergillus, Aureobacterium, Aureobasidium, Bacteroides, Basidiobolus, Beauveria, Blastocystis, Branhamella, Calymmatobacterium, Candida, Capnocytophaga, Catabacter, Chaetomium, Chryseobacterium, Chryseomonas, Chrysonilia, Cladophialophora, Cladosporium, Conidiobolus, Cryptococcus, Curvularia, Exophiala, Exserohilum, Flavobacterium, Fonsecaea, Fusarium, Fusobacterium, Hendersonula, Hypomyces, Koserella, Lelliottia, Leptosphaeria, Leptotrichia, Malassezia, Malbranchea, Mortierella, Mucor, Mycocentrospora, Mycoplasma, Nectria, Ochroconis, Oidiodendron, Phoma, Piedraia, Pithomyces, Pityrosporum, Prevotella,\Pseudallescheria, Rhizomucor, Rhizopus, Rhodotorula, Scolecobasidium, Scopulariopsis, Scytalidium,Sporobolomyces, Stachybotrys, Stomatococcus, Treponema, Trichoderma, Trichophyton, Trichosporon, Tritirachium or Ureaplasma. Group 3 consists of all other microorganisms.
                                    
@@ -488,6 +491,8 @@ This package contains the complete taxonomic tree of almost all microorganisms (
 
 # other --------------------------------------------------------------------
 
+mo_is_yeast(c("Candida", "E. coli"))      # TRUE, FALSE
+
 # gram stains and intrinsic resistance can also be used as a filter in dplyr verbs
 if (require("dplyr")) {
   example_isolates %>%
diff --git a/docs/reference/resistance_predict.html b/docs/reference/resistance_predict.html
index e6a2f9cc..32e3b233 100644
--- a/docs/reference/resistance_predict.html
+++ b/docs/reference/resistance_predict.html
@@ -287,7 +287,7 @@
     
     
       x
-      
                                    a data.frame containing isolates. Can be left blank when used inside dplyr verbs, such as filter(), mutate() and summarise().
                                    
+      
                                    a data.frame containing isolates. Can be left blank for automatic determination.
                                    
     
     
       col_ab
diff --git a/docs/sitemap.xml b/docs/sitemap.xml
index 30f3a701..899189f9 100644
--- a/docs/sitemap.xml
+++ b/docs/sitemap.xml
@@ -66,6 +66,9 @@
   
     https://msberends.github.io/AMR//reference/count.html
   
+  
+    https://msberends.github.io/AMR//reference/dosage.html
+  
   
     https://msberends.github.io/AMR//reference/eucast_rules.html
   
@@ -99,6 +102,9 @@
   
     https://msberends.github.io/AMR//reference/intrinsic_resistant.html
   
+  
+    https://msberends.github.io/AMR//reference/isolate_identifier.html
+  
   
     https://msberends.github.io/AMR//reference/join.html
   
diff --git a/docs/survey.html b/docs/survey.html
index fd727a87..f2a16b68 100644
--- a/docs/survey.html
+++ b/docs/survey.html
@@ -81,7 +81,7 @@
       
       
         AMR (for R)
-        1.5.0
+        1.5.0.9000
       
     
                                  
 
diff --git a/man/antibiotics.Rd b/man/antibiotics.Rd
index 27513775..36df2a43 100644
--- a/man/antibiotics.Rd
+++ b/man/antibiotics.Rd
@@ -4,9 +4,9 @@
 \name{antibiotics}
 \alias{antibiotics}
 \alias{antivirals}
-\title{Data sets with 557 antimicrobials}
+\title{Data sets with 558 antimicrobials}
 \format{
-\subsection{For the \link{antibiotics} data set: a \link{data.frame} with 455 observations and 14 variables:}{
+\subsection{For the \link{antibiotics} data set: a \link{data.frame} with 456 observations and 14 variables:}{
 \itemize{
 \item \code{ab}\cr Antibiotic ID as used in this package (such as \code{AMC}), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available
 \item \code{atc}\cr ATC code (Anatomical Therapeutic Chemical) as defined by the WHOCC, like \code{J01CR02}
diff --git a/man/as.mo.Rd b/man/as.mo.Rd
index 50d26b3c..3e20cf9b 100644
--- a/man/as.mo.Rd
+++ b/man/as.mo.Rd
@@ -143,16 +143,16 @@ If the unlying code needs breaking changes, they will occur gradually. For examp
 
 With ambiguous user input in \code{\link[=as.mo]{as.mo()}} and all the \code{\link[=mo_property]{mo_*}} functions, the returned results are chosen based on their matching score using \code{\link[=mo_matching_score]{mo_matching_score()}}. This matching score \eqn{m}, is calculated as:
 
-\deqn{m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \textrm{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}}{m(x, n) = ( l_n * min(l_n, lev(x, n) ) ) / ( l_n * p_n * k_n )}
+\ifelse{latex}{\deqn{m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \textrm{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}}}{\ifelse{html}{\figure{mo_matching_score.png}{options: width="300px" alt="mo matching score"}}{m(x, n) = ( l_n * min(l_n, lev(x, n) ) ) / ( l_n * p_n * k_n )}}
 
 where:
 \itemize{
-\item \eqn{x} is the user input;
-\item \eqn{n} is a taxonomic name (genus, species, and subspecies);
-\item \eqn{l_n}{l_n} is the length of \eqn{n};
-\item lev is the \href{https://en.wikipedia.org/wiki/Levenshtein_distance}{Levenshtein distance function}, which counts any insertion, deletion and substitution as 1 that is needed to change \eqn{x} into \eqn{n};
-\item \eqn{p_n}{p_n} is the human pathogenic prevalence group of \eqn{n}, as described below;
-\item \eqn{k_n}{p_n} is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.
+\item \ifelse{html}{\out{x is the user input;}}{\eqn{x} is the user input;}
+\item \ifelse{html}{\out{n is a taxonomic name (genus, species, and subspecies);}}{\eqn{n} is a taxonomic name (genus, species, and subspecies);}
+\item \ifelse{html}{\out{ln is the length of n;}}{l_n is the length of \eqn{n};}
+\item \ifelse{html}{\out{lev is the Levenshtein distance function, which counts any insertion, deletion and substitution as 1 that is needed to change x into n;}}{lev is the Levenshtein distance function, which counts any insertion, deletion and substitution as 1 that is needed to change \eqn{x} into \eqn{n};}
+\item \ifelse{html}{\out{pn is the human pathogenic prevalence group of n, as described below;}}{p_n is the human pathogenic prevalence group of \eqn{n}, as described below;}
+\item \ifelse{html}{\out{kn is the taxonomic kingdom of n, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}}{l_n is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}
 }
 
 The grouping into human pathogenic prevalence (\eqn{p}) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. \strong{Group 1} (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is \emph{Enterococcus}, \emph{Staphylococcus} or \emph{Streptococcus}. This group consequently contains all common Gram-negative bacteria, such as \emph{Pseudomonas} and \emph{Legionella} and all species within the order Enterobacterales. \strong{Group 2} consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is \emph{Absidia}, \emph{Acremonium}, \emph{Actinotignum}, \emph{Alternaria}, \emph{Anaerosalibacter}, \emph{Apophysomyces}, \emph{Arachnia}, \emph{Aspergillus}, \emph{Aureobacterium}, \emph{Aureobasidium}, \emph{Bacteroides}, \emph{Basidiobolus}, \emph{Beauveria}, \emph{Blastocystis}, \emph{Branhamella}, \emph{Calymmatobacterium}, \emph{Candida}, \emph{Capnocytophaga}, \emph{Catabacter}, \emph{Chaetomium}, \emph{Chryseobacterium}, \emph{Chryseomonas}, \emph{Chrysonilia}, \emph{Cladophialophora}, \emph{Cladosporium}, \emph{Conidiobolus}, \emph{Cryptococcus}, \emph{Curvularia}, \emph{Exophiala}, \emph{Exserohilum}, \emph{Flavobacterium}, \emph{Fonsecaea}, \emph{Fusarium}, \emph{Fusobacterium}, \emph{Hendersonula}, \emph{Hypomyces}, \emph{Koserella}, \emph{Lelliottia}, \emph{Leptosphaeria}, \emph{Leptotrichia}, \emph{Malassezia}, \emph{Malbranchea}, \emph{Mortierella}, \emph{Mucor}, \emph{Mycocentrospora}, \emph{Mycoplasma}, \emph{Nectria}, \emph{Ochroconis}, \emph{Oidiodendron}, \emph{Phoma}, \emph{Piedraia}, \emph{Pithomyces}, \emph{Pityrosporum}, \emph{Prevotella},\\\emph{Pseudallescheria}, \emph{Rhizomucor}, \emph{Rhizopus}, \emph{Rhodotorula}, \emph{Scolecobasidium}, \emph{Scopulariopsis}, \emph{Scytalidium},\emph{Sporobolomyces}, \emph{Stachybotrys}, \emph{Stomatococcus}, \emph{Treponema}, \emph{Trichoderma}, \emph{Trichophyton}, \emph{Trichosporon}, \emph{Tritirachium} or \emph{Ureaplasma}. \strong{Group 3} consists of all other microorganisms.
diff --git a/man/as.rsi.Rd b/man/as.rsi.Rd
index 99e02870..6a25518b 100755
--- a/man/as.rsi.Rd
+++ b/man/as.rsi.Rd
@@ -67,7 +67,7 @@ is.rsi.eligible(x, threshold = 0.05)
 
 \item{conserve_capped_values}{a logical to indicate that MIC values starting with \code{">"} (but not \code{">="}) must always return "R" , and that MIC values starting with \code{"<"} (but not \code{"<="}) must always return "S"}
 
-\item{add_intrinsic_resistance}{\emph{(only useful when using a EUCAST guideline)} a logical to indicate whether intrinsic antibiotic resistance must also be considered for applicable bug-drug combinations, meaning that e.g. ampicillin will always return "R" in \emph{Klebsiella} species. Determination is based on the \link{intrinsic_resistant} data set, that itself is based on \href{https://www.eucast.org/expert_rules_and_intrinsic_resistance/}{'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2} from 2020.}
+\item{add_intrinsic_resistance}{\emph{(only useful when using a EUCAST guideline)} a logical to indicate whether intrinsic antibiotic resistance must also be considered for applicable bug-drug combinations, meaning that e.g. ampicillin will always return "R" in \emph{Klebsiella} species. Determination is based on the \link{intrinsic_resistant} data set, that itself is based on \href{https://www.eucast.org/expert_rules_and_intrinsic_resistance/}{'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2} (2020).}
 
 \item{reference_data}{a \link{data.frame} to be used for interpretation, which defaults to the \link{rsi_translation} data set. Changing this argument allows for using own interpretation guidelines. This argument must contain a data set that is equal in structure to the \link{rsi_translation} data set (same column names and column types). Please note that the \code{guideline} argument will be ignored when \code{reference_data} is manually set.}
 
diff --git a/man/dosage.Rd b/man/dosage.Rd
new file mode 100644
index 00000000..d449286a
--- /dev/null
+++ b/man/dosage.Rd
@@ -0,0 +1,40 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/data.R
+\docType{data}
+\name{dosage}
+\alias{dosage}
+\title{Data set with treatment dosages as defined by EUCAST}
+\format{
+A \link{data.frame} with 135 observations and 9 variables:
+\itemize{
+\item \code{ab}\cr Antibiotic ID as used in this package (such as \code{AMC}), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available
+\item \code{name}\cr Official name of the antimicrobial agent as used by WHONET/EARS-Net or the WHO
+\item \code{type}\cr Type of the dosage, either "high_dosage", "standard_dosage" or "uncomplicated_uti"
+\item \code{dose}\cr Dose, such as "2 g" or "25 mg/kg"
+\item \code{dose_times}\cr Dose, such as "2 g" or "25 mg/kg"
+\item \code{administration}\cr Route of administration, either "im", "iv" or "oral"
+\item \code{notes}\cr Additional dosage notes
+\item \code{original_txt}\cr Original text in the PDF file of EUCAST
+\item \code{eucast_version}\cr Version number of the EUCAST Clinical Breakpoints guideline to which these dosages apply
+}
+}
+\usage{
+dosage
+}
+\description{
+EUCAST breakpoints used in this package are based on the dosages in this data set. They can be retrieved with \code{\link[=eucast_dosage]{eucast_dosage()}}.
+}
+\details{
+\href{https://www.eucast.org/clinical_breakpoints/}{'EUCAST Clinical Breakpoint Tables' v11.0} (2021) are based on the dosages in this data set.
+}
+\section{Reference data publicly available}{
+
+All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
+}
+
+\section{Read more on our website!}{
+
+On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. As we would like to better understand the backgrounds and needs of our users, please \href{https://msberends.github.io/AMR/survey.html}{participate in our survey}!
+}
+
+\keyword{datasets}
diff --git a/man/eucast_rules.Rd b/man/eucast_rules.Rd
index 6c55fbdb..dd678db0 100644
--- a/man/eucast_rules.Rd
+++ b/man/eucast_rules.Rd
@@ -3,6 +3,7 @@
 \name{eucast_rules}
 \alias{eucast_rules}
 \alias{EUCAST}
+\alias{eucast_dosage}
 \title{Apply EUCAST rules}
 \source{
 \itemize{
@@ -12,6 +13,7 @@ Leclercq et al. \strong{EUCAST expert rules in antimicrobial susceptibility test
 \item EUCAST Intrinsic Resistance and Unusual Phenotypes. Version 3.2, 2020. \href{https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/2020/Intrinsic_Resistance_and_Unusual_Phenotypes_Tables_v3.2_20200225.pdf}{(link)}
 \item EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 9.0, 2019. \href{https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_9.0_Breakpoint_Tables.xlsx}{(link)}
 \item EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 10.0, 2020. \href{https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_10.0_Breakpoint_Tables.xlsx}{(link)}
+\item EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 11.0, 2021. \href{https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_11.0_Breakpoint_Tables.xlsx}{(link)}
 }
 }
 \usage{
@@ -26,6 +28,8 @@ eucast_rules(
   ampc_cephalosporin_resistance = NA,
   ...
 )
+
+eucast_dosage(ab, administration = "iv", version_breakpoints = 11)
 }
 \arguments{
 \item{x}{data with antibiotic columns, such as \code{amox}, \code{AMX} and \code{AMC}}
@@ -38,19 +42,23 @@ eucast_rules(
 
 \item{verbose}{a \link{logical} to turn Verbose mode on and off (default is off). In Verbose mode, the function does not apply rules to the data, but instead returns a data set in logbook form with extensive info about which rows and columns would be effected and in which way. Using Verbose mode takes a lot more time.}
 
-\item{version_breakpoints}{the version number to use for the EUCAST Clinical Breakpoints guideline. Currently supported: 10.0.}
+\item{version_breakpoints}{the version number to use for the EUCAST Clinical Breakpoints guideline. Currently supported: 11.0, 10.0.}
 
 \item{version_expertrules}{the version number to use for the EUCAST Expert Rules and Intrinsic Resistance guideline. Currently supported: 3.1, 3.2.}
 
 \item{ampc_cephalosporin_resistance}{a character value that should be applied for AmpC de-repressed cephalosporin-resistant mutants, defaults to \code{NA}. Currently only works when \code{version_expertrules} is \code{3.2}; '\emph{EUCAST Expert Rules v3.2 on Enterobacterales}' states that susceptible (S) results of cefotaxime, ceftriaxone and ceftazidime should be reported with a note, or results should be suppressed (emptied) for these agents. A value of \code{NA} for this argument will remove results for these agents, while e.g. a value of \code{"R"} will make the results for these agents resistant. Use \code{NULL} to not alter the results for AmpC de-repressed cephalosporin-resistant mutants. \cr For \emph{EUCAST Expert Rules} v3.2, this rule applies to: \emph{Enterobacter, Klebsiella aerogenes, Citrobacter braakii, freundii, gillenii, murliniae, rodenticum, sedlakii, werkmanii, youngae, Hafnia alvei, Serratia, Morganella morganii, Providencia}.}
 
 \item{...}{column name of an antibiotic, please see section \emph{Antibiotics} below}
+
+\item{ab}{any (vector of) text that can be coerced to a valid antibiotic code with \code{\link[=as.ab]{as.ab()}}}
+
+\item{administration}{route of administration, either "im", "iv" or "oral"}
 }
 \value{
 The input of \code{x}, possibly with edited values of antibiotics. Or, if \code{verbose = TRUE}, a \link{data.frame} with all original and new values of the affected bug-drug combinations.
 }
 \description{
-Apply rules for clinical breakpoints and intrinsic resistance as defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST, \url{https://eucast.org}), see \emph{Source}.
+Apply rules for clinical breakpoints and intrinsic resistance as defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST, \url{https://eucast.org}), see \emph{Source}. Use \code{\link[=eucast_dosage]{eucast_dosage()}} to get advised dosages of a certain bug-drug combination, which is based on the \link{dosage} data set.
 
 To improve the interpretation of the antibiogram before EUCAST rules are applied, some non-EUCAST rules can applied at default, see Details.
 }
@@ -140,4 +148,6 @@ b
 # containing all details about the transformations:
 c <- eucast_rules(a, verbose = TRUE)
 }
+
+eucast_dosage(c("tobra", "genta", "cipro"), "iv")
 }
diff --git a/man/filter_ab_class.Rd b/man/filter_ab_class.Rd
index 814c1081..1604a241 100644
--- a/man/filter_ab_class.Rd
+++ b/man/filter_ab_class.Rd
@@ -104,10 +104,11 @@ if (require("dplyr")) {
     filter_aminoglycosides("R", "all") \%>\%
     filter_fluoroquinolones("R", "all")
   
-  # with dplyr 1.0.0 and higher (that adds 'across()'), this is equal:
+  # with dplyr 1.0.0 and higher (that adds 'across()'), this is all equal:
   # (though the row names on the first are more correct)
   example_isolates \%>\% filter_carbapenems("R", "all")
   example_isolates \%>\% filter(across(carbapenems(), ~. == "R"))
+  example_isolates \%>\% filter(across(carbapenems(), function(x) x == "R"))
 }
 }
 }
diff --git a/man/first_isolate.Rd b/man/first_isolate.Rd
index b2a7bc87..730fd4f6 100755
--- a/man/first_isolate.Rd
+++ b/man/first_isolate.Rd
@@ -50,7 +50,7 @@ filter_first_weighted_isolate(
 )
 }
 \arguments{
-\item{x}{a \link{data.frame} containing isolates. Can be left blank when used inside \code{dplyr} verbs, such as \code{\link[dplyr:filter]{filter()}}, \code{\link[dplyr:mutate]{mutate()}} and \code{\link[dplyr:summarise]{summarise()}}.}
+\item{x}{a \link{data.frame} containing isolates. Can be left blank for automatic determination.}
 
 \item{col_date}{column name of the result date (or date that is was received on the lab), defaults to the first column with a date class}
 
diff --git a/man/intrinsic_resistant.Rd b/man/intrinsic_resistant.Rd
index 1013a91c..f0a9673a 100644
--- a/man/intrinsic_resistant.Rd
+++ b/man/intrinsic_resistant.Rd
@@ -20,7 +20,7 @@ Data set containing defined intrinsic resistance by EUCAST of all bug-drug combi
 \details{
 The repository of this \code{AMR} package contains a file comprising this exact data set: \url{https://github.com/msberends/AMR/blob/master/data-raw/intrinsic_resistant.txt}. This file \strong{allows for machine reading EUCAST guidelines about intrinsic resistance}, which is almost impossible with the Excel and PDF files distributed by EUCAST. The file is updated automatically.
 
-This data set is based on \href{https://www.eucast.org/expert_rules_and_intrinsic_resistance/}{'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2} from 2020.
+This data set is based on \href{https://www.eucast.org/expert_rules_and_intrinsic_resistance/}{'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2} (2020).
 }
 \section{Reference data publicly available}{
 
diff --git a/man/isolate_identifier.Rd b/man/isolate_identifier.Rd
new file mode 100644
index 00000000..3e91a70c
--- /dev/null
+++ b/man/isolate_identifier.Rd
@@ -0,0 +1,39 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/isolate_identifier.R
+\name{isolate_identifier}
+\alias{isolate_identifier}
+\title{Create identifier of an isolate}
+\usage{
+isolate_identifier(x, col_mo = NULL, cols_ab = NULL)
+}
+\arguments{
+\item{x}{data with antibiotic columns, such as \code{amox}, \code{AMX} and \code{AMC}}
+
+\item{col_mo}{column name of the IDs of the microorganisms (see \code{\link[=as.mo]{as.mo()}}), defaults to the first column of class \code{\link{mo}}. Values will be coerced using \code{\link[=as.mo]{as.mo()}}.}
+
+\item{cols_ab}{a character vector of column names of \code{x}, or (a combination with) an \href{[ab_class()]}{antibiotic selector function}, such as \code{\link[=carbapenems]{carbapenems()}} and \code{\link[=aminoglysides]{aminoglysides()}}}
+}
+\description{
+This function will paste the microorganism code with all antimicrobial results into one string for each row in a data set. This is useful to compare isolates, e.g. between institutions or regions, when there is no genotyping available.
+}
+\section{Maturing lifecycle}{
+
+\if{html}{\figure{lifecycle_maturing.svg}{options: style=margin-bottom:5px} \cr}
+The \link[=lifecycle]{lifecycle} of this function is \strong{maturing}. The unlying code of a maturing function has been roughed out, but finer details might still change. Since this function needs wider usage and more extensive testing, you are very welcome \href{https://github.com/msberends/AMR/issues}{to suggest changes at our repository} or \link[=AMR]{write us an email (see section 'Contact Us')}.
+}
+
+\section{Read more on our website!}{
+
+On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. As we would like to better understand the backgrounds and needs of our users, please \href{https://msberends.github.io/AMR/survey.html}{participate in our survey}!
+}
+
+\examples{
+# automatic selection of microorganism and antibiotics (i.e., all  columns, see ?as.rsi)
+x <- isolate_identifier(example_isolates)
+
+# ignore microorganism codes, only use antimicrobial results
+x <- isolate_identifier(example_isolates, col_mo = FALSE, cols_ab = c("AMX", "TZP", "GEN", "TOB"))
+
+# select antibiotics from certain antibiotic classes
+x <- isolate_identifier(example_isolates, cols_ab = c(carbapenems(), aminoglycosides()))
+}
diff --git a/man/mdro.Rd b/man/mdro.Rd
index 6c8c98ea..a1c16b5f 100644
--- a/man/mdro.Rd
+++ b/man/mdro.Rd
@@ -40,7 +40,7 @@ mdr_cmi2012(x, guideline = "CMI2012", ...)
 eucast_exceptional_phenotypes(x, guideline = "EUCAST", ...)
 }
 \arguments{
-\item{x}{a \link{data.frame} with antibiotics columns, like \code{AMX} or \code{amox}. Can be left blank when used inside \code{dplyr} verbs, such as \code{\link[dplyr:filter]{filter()}}, \code{\link[dplyr:mutate]{mutate()}} and \code{\link[dplyr:summarise]{summarise()}}.}
+\item{x}{a \link{data.frame} with antibiotics columns, like \code{AMX} or \code{amox}. Can be left blank for automatic determination.}
 
 \item{guideline}{a specific guideline to follow. When left empty, the publication by Magiorakos \emph{et al.} (2012, Clinical Microbiology and Infection) will be followed, please see \emph{Details}.}
 
diff --git a/man/microorganisms.Rd b/man/microorganisms.Rd
index 8c90412c..4f7b2c1c 100755
--- a/man/microorganisms.Rd
+++ b/man/microorganisms.Rd
@@ -32,7 +32,12 @@ microorganisms
 A data set containing the microbial taxonomy of six kingdoms from the Catalogue of Life. MO codes can be looked up using \code{\link[=as.mo]{as.mo()}}.
 }
 \details{
-Manually added were:
+Please note that entries are only based on the Catalogue of Life and the LPSN (see below). Since these sources incorporate entries based on (recent) publications in the International Journal of Systematic and Evolutionary Microbiology (IJSEM), it can happen that the year of publication is sometimes later than one might expect.
+
+For example, \emph{Staphylococcus pettenkoferi} was newly named in Diagnostic Microbiology and Infectious Disease in 2002 (PMID 12106949), but it was not before 2007 that a publication in IJSEM followed (PMID 17625191). Consequently, the AMR package returns 2007 for \code{mo_year("S. pettenkoferi")}.
+\subsection{Manually additions}{
+
+For convenience, some entries were added manually:
 \itemize{
 \item 11 entries of \emph{Streptococcus} (beta-haemolytic: groups A, B, C, D, F, G, H, K and unspecified; other: viridans, milleri)
 \item 2 entries of \emph{Staphylococcus} (coagulase-negative (CoNS) and coagulase-positive (CoPS))
@@ -43,6 +48,8 @@ Manually added were:
 \item 6 families under the Enterobacterales order, according to Adeolu \emph{et al.} (2016, PMID 27620848), that are not (yet) in the Catalogue of Life
 \item 7,411 species from the DSMZ (Deutsche Sammlung von Mikroorganismen und Zellkulturen) since the DSMZ contain the latest taxonomic information based on recent publications
 }
+}
+
 \subsection{Direct download}{
 
 This data set is available as 'flat file' for use even without \R - you can find the file here:
diff --git a/man/microorganisms.codes.Rd b/man/microorganisms.codes.Rd
index 236ffb2f..6b5611a0 100644
--- a/man/microorganisms.codes.Rd
+++ b/man/microorganisms.codes.Rd
@@ -3,9 +3,9 @@
 \docType{data}
 \name{microorganisms.codes}
 \alias{microorganisms.codes}
-\title{Data set with 5,583 common microorganism codes}
+\title{Data set with 5,580 common microorganism codes}
 \format{
-A \link{data.frame} with 5,583 observations and 2 variables:
+A \link{data.frame} with 5,580 observations and 2 variables:
 \itemize{
 \item \code{code}\cr Commonly used code of a microorganism
 \item \code{mo}\cr ID of the microorganism in the \link{microorganisms} data set
diff --git a/man/mo_matching_score.Rd b/man/mo_matching_score.Rd
index 9d469c15..bb5f8862 100644
--- a/man/mo_matching_score.Rd
+++ b/man/mo_matching_score.Rd
@@ -18,16 +18,16 @@ This algorithm is used by \code{\link[=as.mo]{as.mo()}} and all the \code{\link[
 
 With ambiguous user input in \code{\link[=as.mo]{as.mo()}} and all the \code{\link[=mo_property]{mo_*}} functions, the returned results are chosen based on their matching score using \code{\link[=mo_matching_score]{mo_matching_score()}}. This matching score \eqn{m}, is calculated as:
 
-\deqn{m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \textrm{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}}{m(x, n) = ( l_n * min(l_n, lev(x, n) ) ) / ( l_n * p_n * k_n )}
+\ifelse{latex}{\deqn{m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \textrm{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}}}{\ifelse{html}{\figure{mo_matching_score.png}{options: width="300px" alt="mo matching score"}}{m(x, n) = ( l_n * min(l_n, lev(x, n) ) ) / ( l_n * p_n * k_n )}}
 
 where:
 \itemize{
-\item \eqn{x} is the user input;
-\item \eqn{n} is a taxonomic name (genus, species, and subspecies);
-\item \eqn{l_n}{l_n} is the length of \eqn{n};
-\item lev is the \href{https://en.wikipedia.org/wiki/Levenshtein_distance}{Levenshtein distance function}, which counts any insertion, deletion and substitution as 1 that is needed to change \eqn{x} into \eqn{n};
-\item \eqn{p_n}{p_n} is the human pathogenic prevalence group of \eqn{n}, as described below;
-\item \eqn{k_n}{p_n} is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.
+\item \ifelse{html}{\out{x is the user input;}}{\eqn{x} is the user input;}
+\item \ifelse{html}{\out{n is a taxonomic name (genus, species, and subspecies);}}{\eqn{n} is a taxonomic name (genus, species, and subspecies);}
+\item \ifelse{html}{\out{ln is the length of n;}}{l_n is the length of \eqn{n};}
+\item \ifelse{html}{\out{lev is the Levenshtein distance function, which counts any insertion, deletion and substitution as 1 that is needed to change x into n;}}{lev is the Levenshtein distance function, which counts any insertion, deletion and substitution as 1 that is needed to change \eqn{x} into \eqn{n};}
+\item \ifelse{html}{\out{pn is the human pathogenic prevalence group of n, as described below;}}{p_n is the human pathogenic prevalence group of \eqn{n}, as described below;}
+\item \ifelse{html}{\out{kn is the taxonomic kingdom of n, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}}{l_n is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}
 }
 
 The grouping into human pathogenic prevalence (\eqn{p}) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. \strong{Group 1} (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is \emph{Enterococcus}, \emph{Staphylococcus} or \emph{Streptococcus}. This group consequently contains all common Gram-negative bacteria, such as \emph{Pseudomonas} and \emph{Legionella} and all species within the order Enterobacterales. \strong{Group 2} consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is \emph{Absidia}, \emph{Acremonium}, \emph{Actinotignum}, \emph{Alternaria}, \emph{Anaerosalibacter}, \emph{Apophysomyces}, \emph{Arachnia}, \emph{Aspergillus}, \emph{Aureobacterium}, \emph{Aureobasidium}, \emph{Bacteroides}, \emph{Basidiobolus}, \emph{Beauveria}, \emph{Blastocystis}, \emph{Branhamella}, \emph{Calymmatobacterium}, \emph{Candida}, \emph{Capnocytophaga}, \emph{Catabacter}, \emph{Chaetomium}, \emph{Chryseobacterium}, \emph{Chryseomonas}, \emph{Chrysonilia}, \emph{Cladophialophora}, \emph{Cladosporium}, \emph{Conidiobolus}, \emph{Cryptococcus}, \emph{Curvularia}, \emph{Exophiala}, \emph{Exserohilum}, \emph{Flavobacterium}, \emph{Fonsecaea}, \emph{Fusarium}, \emph{Fusobacterium}, \emph{Hendersonula}, \emph{Hypomyces}, \emph{Koserella}, \emph{Lelliottia}, \emph{Leptosphaeria}, \emph{Leptotrichia}, \emph{Malassezia}, \emph{Malbranchea}, \emph{Mortierella}, \emph{Mucor}, \emph{Mycocentrospora}, \emph{Mycoplasma}, \emph{Nectria}, \emph{Ochroconis}, \emph{Oidiodendron}, \emph{Phoma}, \emph{Piedraia}, \emph{Pithomyces}, \emph{Pityrosporum}, \emph{Prevotella},\\\emph{Pseudallescheria}, \emph{Rhizomucor}, \emph{Rhizopus}, \emph{Rhodotorula}, \emph{Scolecobasidium}, \emph{Scopulariopsis}, \emph{Scytalidium},\emph{Sporobolomyces}, \emph{Stachybotrys}, \emph{Stomatococcus}, \emph{Treponema}, \emph{Trichoderma}, \emph{Trichophyton}, \emph{Trichosporon}, \emph{Tritirachium} or \emph{Ureaplasma}. \strong{Group 3} consists of all other microorganisms.
@@ -43,6 +43,16 @@ The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stabl
 If the unlying code needs breaking changes, they will occur gradually. For example, a argument will be deprecated and first continue to work, but will emit an message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
 }
 
+\section{Reference data publicly available}{
+
+All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change.
+}
+
+\section{Read more on our website!}{
+
+On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. As we would like to better understand the backgrounds and needs of our users, please \href{https://msberends.github.io/AMR/survey.html}{participate in our survey}!
+}
+
 \examples{
 as.mo("E. coli")
 mo_uncertainties()
diff --git a/man/mo_property.Rd b/man/mo_property.Rd
index 67bca4b9..ad4faedc 100644
--- a/man/mo_property.Rd
+++ b/man/mo_property.Rd
@@ -18,6 +18,7 @@
 \alias{mo_gramstain}
 \alias{mo_is_gram_negative}
 \alias{mo_is_gram_positive}
+\alias{mo_is_yeast}
 \alias{mo_is_intrinsic_resistant}
 \alias{mo_snomed}
 \alias{mo_ref}
@@ -62,6 +63,8 @@ mo_is_gram_negative(x, language = get_locale(), ...)
 
 mo_is_gram_positive(x, language = get_locale(), ...)
 
+mo_is_yeast(x, language = get_locale(), ...)
+
 mo_is_intrinsic_resistant(x, ab, language = get_locale(), ...)
 
 mo_snomed(x, language = get_locale(), ...)
@@ -85,7 +88,7 @@ mo_url(x, open = FALSE, language = get_locale(), ...)
 mo_property(x, property = "fullname", language = get_locale(), ...)
 }
 \arguments{
-\item{x}{any character (vector) that can be coerced to a valid microorganism code with \code{\link[=as.mo]{as.mo()}}. Can be left blank for auto-guessing the column containing microorganism codes when used inside \code{dplyr} verbs, such as \code{\link[dplyr:filter]{filter()}}, \code{\link[dplyr:mutate]{mutate()}} and \code{\link[dplyr:summarise]{summarise()}}, please see \emph{Examples}.}
+\item{x}{any character (vector) that can be coerced to a valid microorganism code with \code{\link[=as.mo]{as.mo()}}. Can be left blank for auto-guessing the column containing microorganism codes if used in a data set, please see \emph{Examples}.}
 
 \item{language}{language of the returned text, defaults to system language (see \code{\link[=get_locale]{get_locale()}}) and can be overwritten by setting the option \code{AMR_locale}, e.g. \code{options(AMR_locale = "de")}, see \link{translate}. Also used to translate text like "no growth". Use \code{language = NULL} or \code{language = ""} to prevent translation.}
 
@@ -123,7 +126,9 @@ Since the top-level of the taxonomy is sometimes referred to as 'kingdom' and so
 
 The Gram stain - \code{\link[=mo_gramstain]{mo_gramstain()}} - will be determined based on the taxonomic kingdom and phylum. According to Cavalier-Smith (2002, \href{https://pubmed.ncbi.nlm.nih.gov/11837318}{PMID 11837318}), who defined subkingdoms Negibacteria and Posibacteria, only these phyla are Posibacteria: Actinobacteria, Chloroflexi, Firmicutes and Tenericutes. These bacteria are considered Gram-positive - all other bacteria are considered Gram-negative. Species outside the kingdom of Bacteria will return a value \code{NA}. Functions \code{\link[=mo_is_gram_negative]{mo_is_gram_negative()}} and \code{\link[=mo_is_gram_positive]{mo_is_gram_positive()}} always return \code{TRUE} or \code{FALSE} (except when the input is \code{NA} or the MO code is \code{UNKNOWN}), thus always return \code{FALSE} for species outside the taxonomic kingdom of Bacteria.
 
-Intrinsic resistance - \code{\link[=mo_is_intrinsic_resistant]{mo_is_intrinsic_resistant()}} - will be determined based on the \link{intrinsic_resistant} data set, which is based on \href{https://www.eucast.org/expert_rules_and_intrinsic_resistance/}{'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2} from 2020. The \code{\link[=mo_is_intrinsic_resistant]{mo_is_intrinsic_resistant()}} can be vectorised over arguments \code{x} (input for microorganisms) and over \code{ab} (input for antibiotics).
+Determination of yeasts - \code{\link[=mo_is_yeast]{mo_is_yeast()}} - will be based on the taxonomic phylum, class and order. Budding yeasts are true fungi of the phylum Ascomycetes, class Saccharomycetes (also called Hemiascomycetes). The true yeasts are separated into one main order Saccharomycetales. For all microorganisms that are in one of those two groups, the function will return \code{TRUE}. It returns \code{FALSE} for all other taxonomic entries.
+
+Intrinsic resistance - \code{\link[=mo_is_intrinsic_resistant]{mo_is_intrinsic_resistant()}} - will be determined based on the \link{intrinsic_resistant} data set, which is based on \href{https://www.eucast.org/expert_rules_and_intrinsic_resistance/}{'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes' v3.2} (2020). The \code{\link[=mo_is_intrinsic_resistant]{mo_is_intrinsic_resistant()}} can be vectorised over arguments \code{x} (input for microorganisms) and over \code{ab} (input for antibiotics).
 
 All output will be \link{translate}d where possible.
 
@@ -141,16 +146,16 @@ If the unlying code needs breaking changes, they will occur gradually. For examp
 
 With ambiguous user input in \code{\link[=as.mo]{as.mo()}} and all the \code{\link[=mo_property]{mo_*}} functions, the returned results are chosen based on their matching score using \code{\link[=mo_matching_score]{mo_matching_score()}}. This matching score \eqn{m}, is calculated as:
 
-\deqn{m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \textrm{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}}{m(x, n) = ( l_n * min(l_n, lev(x, n) ) ) / ( l_n * p_n * k_n )}
+\ifelse{latex}{\deqn{m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \textrm{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}}}{\ifelse{html}{\figure{mo_matching_score.png}{options: width="300px" alt="mo matching score"}}{m(x, n) = ( l_n * min(l_n, lev(x, n) ) ) / ( l_n * p_n * k_n )}}
 
 where:
 \itemize{
-\item \eqn{x} is the user input;
-\item \eqn{n} is a taxonomic name (genus, species, and subspecies);
-\item \eqn{l_n}{l_n} is the length of \eqn{n};
-\item lev is the \href{https://en.wikipedia.org/wiki/Levenshtein_distance}{Levenshtein distance function}, which counts any insertion, deletion and substitution as 1 that is needed to change \eqn{x} into \eqn{n};
-\item \eqn{p_n}{p_n} is the human pathogenic prevalence group of \eqn{n}, as described below;
-\item \eqn{k_n}{p_n} is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.
+\item \ifelse{html}{\out{x is the user input;}}{\eqn{x} is the user input;}
+\item \ifelse{html}{\out{n is a taxonomic name (genus, species, and subspecies);}}{\eqn{n} is a taxonomic name (genus, species, and subspecies);}
+\item \ifelse{html}{\out{ln is the length of n;}}{l_n is the length of \eqn{n};}
+\item \ifelse{html}{\out{lev is the Levenshtein distance function, which counts any insertion, deletion and substitution as 1 that is needed to change x into n;}}{lev is the Levenshtein distance function, which counts any insertion, deletion and substitution as 1 that is needed to change \eqn{x} into \eqn{n};}
+\item \ifelse{html}{\out{pn is the human pathogenic prevalence group of n, as described below;}}{p_n is the human pathogenic prevalence group of \eqn{n}, as described below;}
+\item \ifelse{html}{\out{kn is the taxonomic kingdom of n, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}}{l_n is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.}
 }
 
 The grouping into human pathogenic prevalence (\eqn{p}) is based on experience from several microbiological laboratories in the Netherlands in conjunction with international reports on pathogen prevalence. \strong{Group 1} (most prevalent microorganisms) consists of all microorganisms where the taxonomic class is Gammaproteobacteria or where the taxonomic genus is \emph{Enterococcus}, \emph{Staphylococcus} or \emph{Streptococcus}. This group consequently contains all common Gram-negative bacteria, such as \emph{Pseudomonas} and \emph{Legionella} and all species within the order Enterobacterales. \strong{Group 2} consists of all microorganisms where the taxonomic phylum is Proteobacteria, Firmicutes, Actinobacteria or Sarcomastigophora, or where the taxonomic genus is \emph{Absidia}, \emph{Acremonium}, \emph{Actinotignum}, \emph{Alternaria}, \emph{Anaerosalibacter}, \emph{Apophysomyces}, \emph{Arachnia}, \emph{Aspergillus}, \emph{Aureobacterium}, \emph{Aureobasidium}, \emph{Bacteroides}, \emph{Basidiobolus}, \emph{Beauveria}, \emph{Blastocystis}, \emph{Branhamella}, \emph{Calymmatobacterium}, \emph{Candida}, \emph{Capnocytophaga}, \emph{Catabacter}, \emph{Chaetomium}, \emph{Chryseobacterium}, \emph{Chryseomonas}, \emph{Chrysonilia}, \emph{Cladophialophora}, \emph{Cladosporium}, \emph{Conidiobolus}, \emph{Cryptococcus}, \emph{Curvularia}, \emph{Exophiala}, \emph{Exserohilum}, \emph{Flavobacterium}, \emph{Fonsecaea}, \emph{Fusarium}, \emph{Fusobacterium}, \emph{Hendersonula}, \emph{Hypomyces}, \emph{Koserella}, \emph{Lelliottia}, \emph{Leptosphaeria}, \emph{Leptotrichia}, \emph{Malassezia}, \emph{Malbranchea}, \emph{Mortierella}, \emph{Mucor}, \emph{Mycocentrospora}, \emph{Mycoplasma}, \emph{Nectria}, \emph{Ochroconis}, \emph{Oidiodendron}, \emph{Phoma}, \emph{Piedraia}, \emph{Pithomyces}, \emph{Pityrosporum}, \emph{Prevotella},\\\emph{Pseudallescheria}, \emph{Rhizomucor}, \emph{Rhizopus}, \emph{Rhodotorula}, \emph{Scolecobasidium}, \emph{Scopulariopsis}, \emph{Scytalidium},\emph{Sporobolomyces}, \emph{Stachybotrys}, \emph{Stomatococcus}, \emph{Treponema}, \emph{Trichoderma}, \emph{Trichophyton}, \emph{Trichosporon}, \emph{Tritirachium} or \emph{Ureaplasma}. \strong{Group 3} consists of all other microorganisms.
@@ -268,6 +273,8 @@ mo_fullname("S. pyogenes",
 
 # other --------------------------------------------------------------------
 
+mo_is_yeast(c("Candida", "E. coli"))      # TRUE, FALSE
+
 # gram stains and intrinsic resistance can also be used as a filter in dplyr verbs
 if (require("dplyr")) {
   example_isolates \%>\%
diff --git a/man/resistance_predict.Rd b/man/resistance_predict.Rd
index 00bce888..d26c9623 100644
--- a/man/resistance_predict.Rd
+++ b/man/resistance_predict.Rd
@@ -47,7 +47,7 @@ ggplot_rsi_predict(
 )
 }
 \arguments{
-\item{x}{a \link{data.frame} containing isolates. Can be left blank when used inside \code{dplyr} verbs, such as \code{\link[dplyr:filter]{filter()}}, \code{\link[dplyr:mutate]{mutate()}} and \code{\link[dplyr:summarise]{summarise()}}.}
+\item{x}{a \link{data.frame} containing isolates. Can be left blank for automatic determination.}
 
 \item{col_ab}{column name of \code{x} containing antimicrobial interpretations (\code{"R"}, \code{"I"} and \code{"S"})}
 
diff --git a/tests/testthat.R b/tests/testthat.R
index 09c15c2b..2f895025 100755
--- a/tests/testthat.R
+++ b/tests/testthat.R
@@ -23,10 +23,10 @@
 # how to conduct AMR analysis: https://msberends.github.io/AMR/        #
 # ==================================================================== #
 
+# the testthat package is in Suggests, but very old R versions will not be
+# able to install it. Yet, we want checks in those R versions as well, so
+# only run unit tests in later R versions:
 if (require("testthat")) {
-  # the testthat package is in Suggests, but very old R versions will not be
-  # able to install it. Yet, we want checks in those R versions as well, so
-  # only run unit tests in later R versions:
   library(testthat, warn.conflicts = FALSE)
   library(AMR)
   test_check("AMR")
diff --git a/tests/testthat/test-data.R b/tests/testthat/test-data.R
index 2806bb6c..ddd43d6e 100644
--- a/tests/testthat/test-data.R
+++ b/tests/testthat/test-data.R
@@ -40,14 +40,17 @@ test_that("data sets are valid", {
   expect_true(all(example_isolates$mo %in% microorganisms$mo))
   expect_true(all(microorganisms.translation$mo_new %in% microorganisms$mo))
   expect_true(all(rsi_translation$mo %in% microorganisms$mo))
+  expect_true(all(rsi_translation$ab %in% antibiotics$ab))
   expect_true(all(intrinsic_resistant$microorganism %in% microorganisms$fullname)) # also important for mo_is_intrinsic_resistant()
   expect_true(all(intrinsic_resistant$antibiotic %in% antibiotics$name))
   expect_false(any(is.na(microorganisms.codes$code)))
   expect_false(any(is.na(microorganisms.codes$mo)))
   expect_false(any(microorganisms.translation$mo_old %in% microorganisms$mo))
+  expect_true(all(dosage$ab %in% antibiotics$ab))
+  expect_true(all(dosage$name %in% antibiotics$name))
   
   # antibiotic names must always be coercible to their original AB code
-  expect_identical(antibiotics$ab, as.ab(antibiotics$name))
+  expect_identical(as.ab(antibiotics$name), antibiotics$ab)
   
   # there should be no diacritics (i.e. non ASCII) characters in the datasets (CRAN policy)
   datasets <- data(package = "AMR", envir = asNamespace("AMR"))$results[, "Item"]