mirror of
https://github.com/msberends/AMR.git
synced 2025-05-01 19:03:50 +02:00
(v2.1.1.9241) fix sir
This commit is contained in:
parent
cf91e677c6
commit
579025f678
@ -1,6 +1,6 @@
|
||||
Package: AMR
|
||||
Version: 2.1.1.9240
|
||||
Date: 2025-04-16
|
||||
Version: 2.1.1.9241
|
||||
Date: 2025-04-18
|
||||
Title: Antimicrobial Resistance Data Analysis
|
||||
Description: Functions to simplify and standardise antimicrobial resistance (AMR)
|
||||
data analysis and to work with microbial and antimicrobial properties by
|
||||
|
||||
8
NEWS.md
8
NEWS.md
@ -1,4 +1,4 @@
|
||||
# AMR 2.1.1.9240
|
||||
# AMR 2.1.1.9241
|
||||
|
||||
*(this beta version will eventually become v3.0. We're happy to reach a new major milestone soon, which will be all about the new One Health support! Install this beta using [the instructions here](https://amr-for-r.org/#get-this-package).)*
|
||||
|
||||
@ -46,17 +46,17 @@ This package now supports not only tools for AMR data analysis in clinical setti
|
||||
|
||||
## Changed
|
||||
* SIR interpretation
|
||||
* It is now possible to use column names for argument `ab`, `mo`, and `uti`: `as.sir(..., ab = "column1", mo = "column2", uti = "column3")`. This greatly improves the flexibility for users.
|
||||
* It is now possible to use column names for arguments `guideline`, `ab`, `mo`, and `uti`: `as.sir(..., ab = "column1", mo = "column2", uti = "column3")`. This greatly improves the flexibility for users.
|
||||
* Users can now set their own criteria (using regular expressions) as to what should be considered S, I, R, SDD, and NI.
|
||||
* To get quantitative values, `as.double()` on a `sir` object will return 1 for S, 2 for SDD/I, and 3 for R (NI will become `NA`). Other functions using `sir` classes (e.g., `summary()`) are updated to reflect the change to contain NI and SDD.
|
||||
* Following CLSI interpretation rules, values outside the log2-dilution range will be rounded upwards to the nearest log2-level before interpretation. Only if using a CLSI guideline.
|
||||
* Combined MIC values (e.g., from CLSI) are now supported
|
||||
* The argument `conserve_capped_values` in `as.sir()` has been replaced with `capped_mic_handling`, which allows greater flexibility in handling capped MIC values (`<`, `<=`, `>`, `>=`). The four available options (`"standard"`, `"strict"`, `"relaxed"`, `"inverse"`) provide full control over whether these values should be interpreted conservatively or ignored. Using `conserve_capped_values` is now deprecated and returns a warning.
|
||||
* Added argument `info` so silence all console messages
|
||||
* Added argument `info` to silence all console messages
|
||||
* `antibiogram()` function
|
||||
* Argument `antibiotics` has been renamed to `antimicrobials`. Using `antibiotics` will still work, but now returns a warning.
|
||||
* Added argument `formatting_type` to set any of the 22 options for the formatting of all 'cells'. This defaults to `18` for non-WISCA and `14` for WISCA, changing the output of antibiograms to cells with more info.
|
||||
* For this reason, `add_total_n` is now `FALSE` at default since the denominators are added to the cells for non-WISCA. For WISCA, the denominator is not useful anyway.
|
||||
* For this reason, `add_total_n` is now deprecated and `FALSE` at default since the denominators are added to the cells dependent on the `formatting_type` setting
|
||||
* The `ab_transform` argument now defaults to `"name"`, displaying antibiotic column names instead of codes
|
||||
* Antimicrobial selectors (previously: *antibiotic selectors*)
|
||||
* 'Antibiotic selectors' are now called 'antimicrobial selectors' since their scope is broader than just antibiotics. All documentation have been updated, and `ab_class()` and `ab_selector()` have been replaced with `amr_class()` and `amr_selector()`. The old functions are now deprecated and will be removed in a future version.
|
||||
|
||||
@ -34,9 +34,8 @@
|
||||
#'
|
||||
#' Adhering to previously described approaches (see *Source*) and especially the Bayesian WISCA model (Weighted-Incidence Syndromic Combination Antibiogram) by Bielicki *et al.*, these functions provide flexible output formats including plots and tables, ideal for integration with R Markdown and Quarto reports.
|
||||
#' @param x A [data.frame] containing at least a column with microorganisms and columns with antimicrobial results (class 'sir', see [as.sir()]).
|
||||
#' @param antimicrobials A vector specifying the antimicrobials to include in the antibiogram (see *Examples*). Will be evaluated using [guess_ab_col()]. This can be:
|
||||
#' - Any antimicrobial name or code that matches to a column name in `x`
|
||||
#' - A column name in `x` that contains SIR values
|
||||
#' @param antimicrobials A vector specifying the antimicrobials containing SIR values to include in the antibiogram (see *Examples*). Will be evaluated using [guess_ab_col()]. This can be:
|
||||
#' - Any antimicrobial name or code that could match (see [guess_ab_col()]) to any column in `x`
|
||||
#' - Any [antimicrobial selector][antimicrobial_selectors], such as [aminoglycosides()] or [carbapenems()]
|
||||
#' - A combination of the above, using `c()`, e.g.:
|
||||
#' - `c(aminoglycosides(), "AMP", "AMC")`
|
||||
@ -489,7 +488,7 @@ antibiogram.default <- function(x,
|
||||
}
|
||||
meet_criteria(syndromic_group, allow_class = "character", allow_NULL = TRUE, allow_NA = TRUE)
|
||||
meet_criteria(add_total_n, allow_class = "logical", has_length = 1)
|
||||
if (isTRUE(add_total_n) || !missing(add_total_n)) {
|
||||
if (isTRUE(add_total_n)) {
|
||||
deprecation_warning("add_total_n", "formatting_type", fn = "antibiogram", is_argument = TRUE)
|
||||
}
|
||||
meet_criteria(only_all_tested, allow_class = "logical", has_length = 1)
|
||||
|
||||
12
R/plotting.R
12
R/plotting.R
@ -244,11 +244,13 @@ create_scale_mic <- function(aest, keep_operators, mic_range = NULL, ...) {
|
||||
}
|
||||
scale$transform_df <- function(self, df) {
|
||||
if (!aest %in% colnames(df)) {
|
||||
# support for geom_hline() and geom_vline()
|
||||
if ("yintercept" %in% colnames(df)) {
|
||||
aest_val <- "yintercept"
|
||||
} else if ("xintercept" %in% colnames(df)) {
|
||||
aest_val <- "xintercept"
|
||||
# support for geom_hline(), geom_vline(), etc
|
||||
other_x <- c("xintercept", "xmin", "xmax", "xend", "width")
|
||||
other_y <- c("yintercept", "ymin", "ymax", "yend", "height")
|
||||
if (any(other_y %in% colnames(df))) {
|
||||
aest_val <- intersect(other_y, colnames(df))[1]
|
||||
} else if (any(other_x %in% colnames(df))) {
|
||||
aest_val <- intersect(other_x, colnames(df))[1]
|
||||
} else {
|
||||
stop_("No support for plotting df with `scale_", aest, "_mic()` with columns ", vector_and(colnames(df), sort = FALSE))
|
||||
}
|
||||
|
||||
161
R/sir.R
161
R/sir.R
@ -43,7 +43,7 @@
|
||||
#' @param ab A vector (or column name) with [character]s that can be coerced to a valid antimicrobial drug code with [as.ab()].
|
||||
#' @param uti (Urinary Tract Infection) a vector (or column name) with [logical]s (`TRUE` or `FALSE`) to specify whether a UTI specific interpretation from the guideline should be chosen. For using [as.sir()] on a [data.frame], this can also be a column containing [logical]s or when left blank, the data set will be searched for a column 'specimen', and rows within this column containing 'urin' (such as 'urine', 'urina') will be regarded isolates from a UTI. See *Examples*.
|
||||
#' @inheritParams first_isolate
|
||||
#' @param guideline Defaults to `r AMR::clinical_breakpoints$guideline[1]` (the latest implemented EUCAST guideline in the [AMR::clinical_breakpoints] data set), but can be set with the package option [`AMR_guideline`][AMR-options]. Currently supports EUCAST (`r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`) and CLSI (`r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI")$guideline)))`), see *Details*.
|
||||
#' @param guideline A guideline name (or column name) to use for SIR interpretation. Defaults to `r AMR::clinical_breakpoints$guideline[1]` (the latest implemented EUCAST guideline in the [AMR::clinical_breakpoints] data set), but can be set with the package option [`AMR_guideline`][AMR-options]. Currently supports EUCAST (`r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`) and CLSI (`r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI")$guideline)))`), see *Details*. Using a column name for [as.sir()] allows for easy interpretation on historical data which needs to be interpreted according to e.g., various years.
|
||||
#' @param capped_mic_handling A [character] string that controls how MIC values with a cap (i.e., starting with `<`, `<=`, `>`, or `>=`) are interpreted. Supports the following options:
|
||||
#'
|
||||
#' `"none"`
|
||||
@ -189,7 +189,8 @@
|
||||
#' bacteria = rep("Escherichia coli", 4),
|
||||
#' antibiotic = c("amoxicillin", "cipro", "tobra", "genta"),
|
||||
#' mics = as.mic(c(0.01, 1, 4, 8)),
|
||||
#' disks = as.disk(c(6, 10, 14, 18))
|
||||
#' disks = as.disk(c(6, 10, 14, 18)),
|
||||
#' guideline = c("EUCAST 2021", "EUCAST 2022", "EUCAST 2023", "EUCAST 2024")
|
||||
#' )
|
||||
#'
|
||||
#' \donttest{
|
||||
@ -208,7 +209,7 @@
|
||||
#' mutate_if(is.mic, as.sir,
|
||||
#' mo = "bacteria",
|
||||
#' ab = "antibiotic",
|
||||
#' guideline = "CLSI"
|
||||
#' guideline = guideline
|
||||
#' )
|
||||
#' df_long %>%
|
||||
#' mutate(across(
|
||||
@ -675,7 +676,7 @@ as.sir.data.frame <- function(x,
|
||||
conserve_capped_values = NULL) {
|
||||
meet_criteria(x, allow_class = "data.frame") # will also check for dimensions > 0
|
||||
meet_criteria(col_mo, allow_class = "character", is_in = colnames(x), allow_NULL = TRUE)
|
||||
meet_criteria(guideline, allow_class = "character", has_length = 1)
|
||||
meet_criteria(guideline, allow_class = "character")
|
||||
meet_criteria(uti, allow_class = c("logical", "character"), allow_NULL = TRUE, allow_NA = TRUE)
|
||||
meet_criteria(capped_mic_handling, allow_class = "character", has_length = 1, is_in = c("standard", "conservative", "none", "inverse"))
|
||||
meet_criteria(add_intrinsic_resistance, allow_class = "logical", has_length = 1)
|
||||
@ -908,14 +909,13 @@ get_guideline <- function(guideline, reference_data) {
|
||||
if (!identical(reference_data, AMR::clinical_breakpoints)) {
|
||||
return(guideline)
|
||||
}
|
||||
guideline_param <- toupper(guideline)
|
||||
if (guideline_param %in% c("CLSI", "EUCAST")) {
|
||||
guideline_param <- rev(sort(subset(reference_data, guideline %like% guideline_param)$guideline))[1L]
|
||||
}
|
||||
if (guideline_param %unlike% " ") {
|
||||
guideline_param <- trimws2(toupper(guideline))
|
||||
latest_clsi <- rev(sort(subset(reference_data, guideline %like% "CLSI")$guideline))[1L]
|
||||
latest_eucast <- rev(sort(subset(reference_data, guideline %like% "EUCAST")$guideline))[1L]
|
||||
guideline_param[guideline_param == "CLSI"] <- latest_clsi
|
||||
guideline_param[guideline_param == "EUCAST"] <- latest_eucast
|
||||
# like 'EUCAST2020', should be 'EUCAST 2020'
|
||||
guideline_param <- gsub("([a-z]+)([0-9]+)", "\\1 \\2", guideline_param, ignore.case = TRUE)
|
||||
}
|
||||
guideline_param[guideline_param %unlike% " "] <- gsub("([a-z]+)([0-9]+)", "\\1 \\2", guideline_param[guideline_param %unlike% " "], ignore.case = TRUE)
|
||||
|
||||
stop_ifnot(guideline_param %in% reference_data$guideline,
|
||||
"invalid guideline: '", guideline,
|
||||
@ -988,7 +988,7 @@ as_sir_method <- function(method_short,
|
||||
meet_criteria(x, allow_NA = TRUE, .call_depth = -2)
|
||||
meet_criteria(mo, allow_class = c("mo", "character"), has_length = c(1, length(x)), allow_NULL = TRUE, .call_depth = -2)
|
||||
meet_criteria(ab, allow_class = c("ab", "character"), has_length = c(1, length(x)), .call_depth = -2)
|
||||
meet_criteria(guideline, allow_class = "character", has_length = 1, .call_depth = -2)
|
||||
meet_criteria(guideline, allow_class = "character", has_length = c(1, length(x)), .call_depth = -2)
|
||||
meet_criteria(uti, allow_class = c("logical", "character"), has_length = c(1, length(x)), allow_NULL = TRUE, allow_NA = TRUE, .call_depth = -2)
|
||||
meet_criteria(capped_mic_handling, allow_class = "character", has_length = 1, is_in = c("standard", "conservative", "none", "inverse"), .call_depth = -2)
|
||||
meet_criteria(add_intrinsic_resistance, allow_class = "logical", has_length = 1, .call_depth = -2)
|
||||
@ -1011,8 +1011,6 @@ as_sir_method <- function(method_short,
|
||||
|
||||
current_sir_interpretation_history <- NROW(AMR_env$sir_interpretation_history)
|
||||
|
||||
guideline_coerced <- get_guideline(guideline, reference_data)
|
||||
|
||||
if (isTRUE(info) && message_not_thrown_before("as.sir", "sir_interpretation_history")) {
|
||||
message()
|
||||
message_("Run `sir_interpretation_history()` afterwards to retrieve a logbook with all the details of the breakpoint interpretations.\n\n", add_fn = font_green)
|
||||
@ -1020,6 +1018,12 @@ as_sir_method <- function(method_short,
|
||||
|
||||
current_df <- tryCatch(get_current_data(NA, 0), error = function(e) NULL)
|
||||
|
||||
# get guideline
|
||||
if (!is.null(current_df) && length(guideline) == 1 && guideline %in% colnames(current_df) && any(current_df[[guideline]] %like% "CLSI|EUCAST", na.rm = TRUE)) {
|
||||
guideline <- current_df[[guideline]]
|
||||
}
|
||||
guideline_coerced <- get_guideline(guideline, reference_data)
|
||||
|
||||
# get host
|
||||
if (breakpoint_type == "animal") {
|
||||
if (is.null(host)) {
|
||||
@ -1215,7 +1219,7 @@ as_sir_method <- function(method_short,
|
||||
ifelse(length(unique(agent_formatted)) == 1, unique(agent_formatted), paste0(vector_and(agent_formatted, quotes = FALSE, sort = FALSE))),
|
||||
mo_var_found,
|
||||
ifelse(identical(reference_data, AMR::clinical_breakpoints),
|
||||
paste0(", ", font_bold(guideline_coerced)),
|
||||
paste0(", ", vector_and(font_bold(guideline_coerced, collapse = NULL), quotes = FALSE)),
|
||||
""
|
||||
),
|
||||
"... "
|
||||
@ -1233,11 +1237,11 @@ as_sir_method <- function(method_short,
|
||||
|
||||
if (identical(reference_data, AMR::clinical_breakpoints)) {
|
||||
breakpoints <- reference_data %pm>%
|
||||
subset(guideline == guideline_coerced & method == method_coerced & ab %in% ab_coerced)
|
||||
subset(guideline %in% guideline_coerced & method == method_coerced & ab %in% ab_coerced)
|
||||
if (any(ab_coerced == "AMX") && nrow(breakpoints[breakpoints$ab == "AMX", , drop = FALSE]) == 0) {
|
||||
ab_coerced[ab_coerced == "AMX"] <- "AMP"
|
||||
breakpoints <- reference_data %pm>%
|
||||
subset(guideline == guideline_coerced & method == method_coerced & ab %in% ab_coerced)
|
||||
subset(guideline %in% guideline_coerced & method == method_coerced & ab %in% ab_coerced)
|
||||
}
|
||||
} else {
|
||||
breakpoints <- reference_data %pm>%
|
||||
@ -1249,6 +1253,7 @@ as_sir_method <- function(method_short,
|
||||
df <- data.frame(
|
||||
values = x,
|
||||
values_bak = x,
|
||||
guideline = guideline_coerced,
|
||||
mo = mo,
|
||||
ab = ab,
|
||||
result = NA_sir_,
|
||||
@ -1257,12 +1262,12 @@ as_sir_method <- function(method_short,
|
||||
stringsAsFactors = FALSE
|
||||
)
|
||||
if (method == "mic") {
|
||||
if (guideline %like% "CLSI") {
|
||||
if (any(guideline_coerced %like% "CLSI")) {
|
||||
# CLSI says: if MIC is not a log2 value it must be rounded up to the nearest log2 value
|
||||
log2_levels <- 2^c(-9:12)
|
||||
df$values <- vapply(
|
||||
df$values[which(df$guideline %like% "CLSI")] <- vapply(
|
||||
FUN.VALUE = character(1),
|
||||
df$values,
|
||||
df$values[which(df$guideline %like% "CLSI")],
|
||||
function(mic_val) {
|
||||
if (is.na(mic_val)) {
|
||||
return(NA_character_)
|
||||
@ -1282,13 +1287,12 @@ as_sir_method <- function(method_short,
|
||||
)
|
||||
}
|
||||
df$values <- as.mic(df$values)
|
||||
print(df)
|
||||
} else if (method == "disk") {
|
||||
# when as.sir.disk is called directly
|
||||
df$values <- as.disk(df$values)
|
||||
}
|
||||
|
||||
df_unique <- unique(df[, c("mo", "ab", "uti", "host"), drop = FALSE])
|
||||
df_unique <- unique(df[, c("guideline", "mo", "ab", "uti", "host"), drop = FALSE])
|
||||
mo_grams <- suppressWarnings(suppressMessages(mo_gramstain(df_unique$mo, language = NULL, keep_synonyms = FALSE)))
|
||||
|
||||
# get all breakpoints, use humans as backup for animals
|
||||
@ -1312,7 +1316,7 @@ as_sir_method <- function(method_short,
|
||||
|
||||
notes <- character(0)
|
||||
|
||||
if (guideline_coerced %like% "EUCAST") {
|
||||
if (any(guideline_coerced %like% "EUCAST")) {
|
||||
any_is_intrinsic_resistant <- FALSE
|
||||
add_intrinsic_resistance_to_AMR_env()
|
||||
}
|
||||
@ -1331,7 +1335,7 @@ as_sir_method <- function(method_short,
|
||||
message(
|
||||
paste0(font_rose_bg(" WARNING "), "\n"),
|
||||
font_black(paste0(
|
||||
" ", AMR_env$bullet_icon, " No ", guideline_coerced, " ", method_coerced, " breakpoints available for ",
|
||||
" ", AMR_env$bullet_icon, " No ", method_coerced, " breakpoints available for ",
|
||||
suppressMessages(suppressWarnings(ab_name(unique(ab_coerced), language = NULL, tolower = TRUE))),
|
||||
" (", unique(ab_coerced), ")."
|
||||
), collapse = "\n")
|
||||
@ -1353,24 +1357,26 @@ as_sir_method <- function(method_short,
|
||||
# run the rules (df_unique is a row combination per mo/ab/uti/host) ----
|
||||
for (i in seq_len(nrow(df_unique))) {
|
||||
p$tick()
|
||||
guideline_current <- df_unique[i, "guideline", drop = TRUE]
|
||||
mo_current <- df_unique[i, "mo", drop = TRUE]
|
||||
mo_gram_current <- mo_grams[i]
|
||||
ab_current <- df_unique[i, "ab", drop = TRUE]
|
||||
host_current <- df_unique[i, "host", drop = TRUE]
|
||||
uti_current <- df_unique[i, "uti", drop = TRUE]
|
||||
notes_current <- character(0)
|
||||
if (is.na(uti_current)) {
|
||||
# no preference, so no filter on UTIs
|
||||
rows <- which(as.character(df$mo) == mo_current & df$ab == ab_current & df$host == host_current)
|
||||
} else {
|
||||
rows <- which(as.character(df$mo) == mo_current & df$ab == ab_current & df$host == host_current & df$uti == uti_current)
|
||||
rows <- which(as.character(df$mo) == mo_current & df$ab == ab_current & df$host == host_current & df$guideline == guideline_current)
|
||||
if (!is.na(uti_current)) {
|
||||
# also filter on UTIs
|
||||
rows <- rows[df$uti[rows] == uti_current]
|
||||
}
|
||||
|
||||
if (length(rows) == 0) {
|
||||
# this can happen if a host is unavailable, just continue with the next one, since a note about hosts having NA are already given at this point
|
||||
next
|
||||
}
|
||||
values <- df[rows, "values", drop = TRUE]
|
||||
values_bak <- df[rows, "values_bak", drop = TRUE]
|
||||
notes_current <- rep("", length(rows))
|
||||
new_sir <- rep(NA_sir_, length(rows))
|
||||
|
||||
# find different mo properties, as fast as possible
|
||||
@ -1415,7 +1421,7 @@ as_sir_method <- function(method_short,
|
||||
# gather all available breakpoints for current MO
|
||||
# TODO for VET09 do not filter out E. coli and such
|
||||
breakpoints_current <- breakpoints %pm>%
|
||||
subset(ab == ab_current) %pm>%
|
||||
subset(ab == ab_current & guideline == guideline_current) %pm>%
|
||||
subset(mo %in% c(
|
||||
mo_current, mo_current_genus, mo_current_family,
|
||||
mo_current_order, mo_current_class,
|
||||
@ -1424,6 +1430,7 @@ as_sir_method <- function(method_short,
|
||||
mo_current_other
|
||||
))
|
||||
|
||||
|
||||
# TODO are operators considered??
|
||||
# This seems to not work well: as.sir(as.mic(c(4, ">4", ">=4", 8, ">8", ">=8")), ab = "AMC", mo = "E. coli", breakpoint_type = "animal", host = "dogs", guideline = "CLSI 2024")
|
||||
|
||||
@ -1515,8 +1522,8 @@ as_sir_method <- function(method_short,
|
||||
host = vectorise_log_entry(host_current, length(rows)),
|
||||
input = vectorise_log_entry(as.character(values), length(rows)),
|
||||
outcome = vectorise_log_entry(NA_sir_, length(rows)),
|
||||
notes = vectorise_log_entry("NO BREAKPOINT AVAILABLE", length(rows)),
|
||||
guideline = vectorise_log_entry(guideline_coerced, length(rows)),
|
||||
notes = vectorise_log_entry("No breakpoint available", length(rows)),
|
||||
guideline = vectorise_log_entry(guideline_current, length(rows)),
|
||||
ref_table = vectorise_log_entry(NA_character_, length(rows)),
|
||||
uti = vectorise_log_entry(uti_current, length(rows)),
|
||||
breakpoint_S_R = vectorise_log_entry(NA_character_, length(rows)),
|
||||
@ -1556,21 +1563,33 @@ as_sir_method <- function(method_short,
|
||||
}
|
||||
if (nrow(breakpoints_current) == 1 && all(breakpoints_current$uti == TRUE) && is.na(uti_current) && message_not_thrown_before("as.sir", "uti", ab_current)) {
|
||||
# only UTI breakpoints available
|
||||
notes_current <- c(notes_current, paste0("Breakpoints for ", font_bold(ab_formatted), " in ", mo_formatted, " are only available for (uncomplicated) urinary tract infections (UTI); assuming `uti = TRUE`."))
|
||||
notes_current <- paste0(
|
||||
notes_current, "\n",
|
||||
paste0("Breakpoints for ", font_bold(ab_formatted), " in ", mo_formatted, " are only available for (uncomplicated) urinary tract infections (UTI); assuming `uti = TRUE`.")
|
||||
)
|
||||
} else if (nrow(breakpoints_current) > 1 && length(unique(breakpoints_current$site)) > 1 && any(is.na(uti_current)) && all(c(TRUE, FALSE) %in% breakpoints_current$uti, na.rm = TRUE) && message_not_thrown_before("as.sir", "siteUTI", mo_current, ab_current)) {
|
||||
# both UTI and Non-UTI breakpoints available
|
||||
notes_current <- c(notes_current, paste0("Breakpoints for UTI ", font_bold("and"), " non-UTI available for ", ab_formatted, " in ", mo_formatted, " - assuming ", site, ". Use argument `uti` to set which isolates are from urine. See `?as.sir`."))
|
||||
breakpoints_current <- breakpoints_current %pm>%
|
||||
pm_filter(uti == FALSE)
|
||||
notes_current <- paste0(
|
||||
notes_current, "\n",
|
||||
paste0("Breakpoints for UTI ", font_bold("and"), " non-UTI available for ", ab_formatted, " in ", mo_formatted, " - assuming ", site, ". Use argument `uti` to set which isolates are from urine. See `?as.sir`.")
|
||||
)
|
||||
} else if (nrow(breakpoints_current) > 1 && length(unique(breakpoints_current$site)) > 1 && all(breakpoints_current$uti == FALSE, na.rm = TRUE) && message_not_thrown_before("as.sir", "siteOther", mo_current, ab_current)) {
|
||||
# breakpoints for multiple body sites available
|
||||
notes_current <- c(notes_current, paste0("Multiple breakpoints available for ", font_bold(ab_formatted), " in ", mo_formatted, " - assuming ", site, "."))
|
||||
notes_current <- paste0(
|
||||
notes_current, "\n",
|
||||
paste0("Multiple breakpoints available for ", font_bold(ab_formatted), " in ", mo_formatted, " - assuming ", site, ".")
|
||||
)
|
||||
}
|
||||
|
||||
# first check if mo is intrinsic resistant
|
||||
if (isTRUE(add_intrinsic_resistance) && guideline_coerced %like% "EUCAST" && paste(mo_current, ab_current) %in% AMR_env$intrinsic_resistant) {
|
||||
notes_current <- c(notes_current, paste0("Intrinsic resistance applied for ", ab_formatted, " in ", mo_formatted, ""))
|
||||
if (isTRUE(add_intrinsic_resistance) && guideline_current %like% "EUCAST" && paste(mo_current, ab_current) %in% AMR_env$intrinsic_resistant) {
|
||||
new_sir <- rep(as.sir("R"), length(rows))
|
||||
notes_current <- paste0(
|
||||
notes_current, "\n",
|
||||
paste0("Intrinsic resistance applied for ", ab_formatted, " in ", mo_formatted, "")
|
||||
)
|
||||
} else if (nrow(breakpoints_current) == 0) {
|
||||
# no rules available
|
||||
new_sir <- rep(NA_sir_, length(rows))
|
||||
@ -1578,24 +1597,43 @@ as_sir_method <- function(method_short,
|
||||
# then run the rules
|
||||
breakpoints_current <- breakpoints_current[1L, , drop = FALSE]
|
||||
|
||||
if (any(breakpoints_current$mo == "UNKNOWN", na.rm = TRUE) | any(breakpoints_current$ref_tbl %like% "PK.*PD", na.rm = TRUE)) {
|
||||
notes_current <- c(notes_current, "Some PK/PD breakpoints were applied - use `include_PKPD = FALSE` to prevent this")
|
||||
}
|
||||
if (any(breakpoints_current$site %like% "screen", na.rm = TRUE) | any(breakpoints_current$ref_tbl %like% "screen", na.rm = TRUE)) {
|
||||
notes_current <- c(notes_current, "Some screening breakpoints were applied - use `include_screening = FALSE` to prevent this")
|
||||
}
|
||||
if (method == "mic" && capped_mic_handling %in% c("conservative", "inverse") && any(as.character(values_bak) %like% "^[<][0-9]")) {
|
||||
notes_current <- c(notes_current, paste0("MIC values with the sign '<' are all considered 'S' since capped_mic_handling = \"", capped_mic_handling, "\""))
|
||||
}
|
||||
if (method == "mic" && capped_mic_handling %in% c("conservative", "inverse") && any(as.character(values_bak) %like% "^[>][0-9]")) {
|
||||
notes_current <- c(notes_current, paste0("MIC values with the sign '>' are all considered 'R' since capped_mic_handling = \"", capped_mic_handling, "\""))
|
||||
}
|
||||
if (method == "mic" && capped_mic_handling %in% c("conservative", "standard") && any(as.character(values_bak) %like% "^[><]=[0-9]" & as.double(values) > breakpoints_current$breakpoint_S & as.double(values) < breakpoints_current$breakpoint_R, na.rm = TRUE)) {
|
||||
notes_current <- c(notes_current, paste0("MIC values within the breakpoint guideline range with the sign '<=' or '>=' are considered 'NI' since capped_mic_handling = \"", capped_mic_handling, "\""))
|
||||
}
|
||||
notes_current <- paste0(
|
||||
notes_current, "\n",
|
||||
ifelse(breakpoints_current$mo == "UNKNOWN" | breakpoints_current$ref_tbl %like% "PK.*PD",
|
||||
"Some PK/PD breakpoints were applied - use `include_PKPD = FALSE` to prevent this",
|
||||
""
|
||||
),
|
||||
"\n",
|
||||
ifelse(breakpoints_current$site %like% "screen" | breakpoints_current$ref_tbl %like% "screen",
|
||||
"Some screening breakpoints were applied - use `include_screening = FALSE` to prevent this",
|
||||
""
|
||||
),
|
||||
"\n",
|
||||
ifelse(method == "mic" & capped_mic_handling %in% c("conservative", "inverse") & as.character(values_bak) %like% "^[<][0-9]",
|
||||
paste0("MIC values with the sign '<' are all considered 'S' since capped_mic_handling = \"", capped_mic_handling, "\""),
|
||||
""
|
||||
),
|
||||
"\n",
|
||||
ifelse(method == "mic" & capped_mic_handling %in% c("conservative", "inverse") & as.character(values_bak) %like% "^[>][0-9]",
|
||||
paste0("MIC values with the sign '>' are all considered 'R' since capped_mic_handling = \"", capped_mic_handling, "\""),
|
||||
""
|
||||
),
|
||||
"\n",
|
||||
ifelse(method == "mic" & capped_mic_handling %in% c("conservative", "standard") & as.character(values_bak) %like% "^[><]=[0-9]" & as.double(values) > breakpoints_current$breakpoint_S & as.double(values) < breakpoints_current$breakpoint_R,
|
||||
paste0("MIC values within the breakpoint guideline range with the sign '<=' or '>=' are considered 'NI' since capped_mic_handling = \"", capped_mic_handling, "\""),
|
||||
""
|
||||
)
|
||||
)
|
||||
if (isTRUE(substitute_missing_r_breakpoint) && !is.na(breakpoints_current$breakpoint_S) && is.na(breakpoints_current$breakpoint_R)) {
|
||||
breakpoints_current$breakpoint_R <- breakpoints_current$breakpoint_S # breakpoints_current only has 1 row at this moment
|
||||
notes_current <- c(notes_current, "NAs because of missing R breakpoints were substituted with R since substitute_missing_r_breakpoint = TRUE")
|
||||
# breakpoints_current only has 1 row at this moment
|
||||
breakpoints_current$breakpoint_R <- breakpoints_current$breakpoint_S
|
||||
notes_current <- paste0(
|
||||
notes_current, "\n",
|
||||
ifelse(!is.na(breakpoints_current$breakpoint_S) & is.na(breakpoints_current$breakpoint_R),
|
||||
"NAs because of missing R breakpoints were substituted with R since substitute_missing_r_breakpoint = TRUE",
|
||||
""
|
||||
)
|
||||
)
|
||||
}
|
||||
|
||||
if (method == "mic") {
|
||||
@ -1605,8 +1643,8 @@ as_sir_method <- function(method_short,
|
||||
capped_mic_handling %in% c("conservative", "inverse") & as.character(values_bak) %like% "^[>][0-9]" ~ as.sir("R"),
|
||||
capped_mic_handling %in% c("conservative", "standard") & as.character(values_bak) %like% "^[><]=[0-9]" & as.double(values) > breakpoints_current$breakpoint_S & as.double(values) < breakpoints_current$breakpoint_R ~ as.sir("NI"),
|
||||
values <= breakpoints_current$breakpoint_S ~ as.sir("S"),
|
||||
guideline_coerced %like% "EUCAST" & values > breakpoints_current$breakpoint_R ~ as.sir("R"),
|
||||
guideline_coerced %like% "CLSI" & values >= breakpoints_current$breakpoint_R ~ as.sir("R"),
|
||||
guideline_current %like% "EUCAST" & values > breakpoints_current$breakpoint_R ~ as.sir("R"),
|
||||
guideline_current %like% "CLSI" & values >= breakpoints_current$breakpoint_R ~ as.sir("R"),
|
||||
# return "I" or "SDD" when breakpoints are in the middle
|
||||
!is.na(breakpoints_current$breakpoint_S) & !is.na(breakpoints_current$breakpoint_R) & breakpoints_current$is_SDD == TRUE ~ as.sir("SDD"),
|
||||
!is.na(breakpoints_current$breakpoint_S) & !is.na(breakpoints_current$breakpoint_R) & breakpoints_current$is_SDD == FALSE ~ as.sir("I"),
|
||||
@ -1617,8 +1655,8 @@ as_sir_method <- function(method_short,
|
||||
new_sir <- case_when_AMR(
|
||||
is.na(values) ~ NA_sir_,
|
||||
as.double(values) >= as.double(breakpoints_current$breakpoint_S) ~ as.sir("S"),
|
||||
guideline_coerced %like% "EUCAST" & as.double(values) < as.double(breakpoints_current$breakpoint_R) ~ as.sir("R"),
|
||||
guideline_coerced %like% "CLSI" & as.double(values) <= as.double(breakpoints_current$breakpoint_R) ~ as.sir("R"),
|
||||
guideline_current %like% "EUCAST" & as.double(values) < as.double(breakpoints_current$breakpoint_R) ~ as.sir("R"),
|
||||
guideline_current %like% "CLSI" & as.double(values) <= as.double(breakpoints_current$breakpoint_R) ~ as.sir("R"),
|
||||
# return "I" or "SDD" when breakpoints are in the middle
|
||||
!is.na(breakpoints_current$breakpoint_S) & !is.na(breakpoints_current$breakpoint_R) & breakpoints_current$is_SDD == TRUE ~ as.sir("SDD"),
|
||||
!is.na(breakpoints_current$breakpoint_S) & !is.na(breakpoints_current$breakpoint_R) & breakpoints_current$is_SDD == FALSE ~ as.sir("I"),
|
||||
@ -1628,6 +1666,8 @@ as_sir_method <- function(method_short,
|
||||
}
|
||||
|
||||
# write to verbose output
|
||||
notes_current <- trimws2(notes_current)
|
||||
notes_current[notes_current == ""] <- NA_character_
|
||||
AMR_env$sir_interpretation_history <- rbind_AMR(
|
||||
AMR_env$sir_interpretation_history,
|
||||
# recycling 1 to 2 rows does not always seem to work, which is why vectorise_log_entry() was added
|
||||
@ -1644,8 +1684,8 @@ as_sir_method <- function(method_short,
|
||||
host = vectorise_log_entry(breakpoints_current[, "host", drop = TRUE], length(rows)),
|
||||
input = vectorise_log_entry(as.character(values), length(rows)),
|
||||
outcome = vectorise_log_entry(as.sir(new_sir), length(rows)),
|
||||
notes = vectorise_log_entry(paste0(font_stripstyle(notes_current), collapse = "\n"), length(rows)),
|
||||
guideline = vectorise_log_entry(guideline_coerced, length(rows)),
|
||||
notes = font_stripstyle(notes_current), # vectorise_log_entry(paste0(font_stripstyle(notes_current), collapse = "\n"), length(rows)),
|
||||
guideline = vectorise_log_entry(guideline_current, length(rows)),
|
||||
ref_table = vectorise_log_entry(breakpoints_current[, "ref_tbl", drop = TRUE], length(rows)),
|
||||
uti = vectorise_log_entry(breakpoints_current[, "uti", drop = TRUE], length(rows)),
|
||||
breakpoint_S_R = vectorise_log_entry(paste0(breakpoints_current[, "breakpoint_S", drop = TRUE], "-", breakpoints_current[, "breakpoint_R", drop = TRUE]), length(rows)),
|
||||
@ -1665,6 +1705,7 @@ as_sir_method <- function(method_short,
|
||||
# the progress bar has overwritten the intro text, so:
|
||||
message_(intro_txt, appendLF = FALSE, as_note = FALSE)
|
||||
}
|
||||
notes <- notes[!trimws2(notes) %in% c("", NA_character_)]
|
||||
if (length(notes) > 0) {
|
||||
if (isTRUE(rise_warning)) {
|
||||
message(font_rose_bg(" WARNING "))
|
||||
|
||||
@ -1,6 +1,6 @@
|
||||
This knowledge base contains all context you must know about the AMR package for R. You are a GPT trained to be an assistant for the AMR package in R. You are an incredible R specialist, especially trained in this package and in the tidyverse.
|
||||
|
||||
First and foremost, you are trained on version 2.1.1.9240. Remember this whenever someone asks which AMR package version you’re at.
|
||||
First and foremost, you are trained on version 2.1.1.9241. Remember this whenever someone asks which AMR package version you’re at.
|
||||
|
||||
Below are the contents of the NAMESPACE file, the index.md file, and all the man/*.Rd files (documentation) in the package. Every file content is split using 100 hypens.
|
||||
----------------------------------------------------------------------------------------------------
|
||||
@ -1723,10 +1723,9 @@ retrieve_wisca_parameters(wisca_model, ...)
|
||||
\arguments{
|
||||
\item{x}{A \link{data.frame} containing at least a column with microorganisms and columns with antimicrobial results (class 'sir', see \code{\link[=as.sir]{as.sir()}}).}
|
||||
|
||||
\item{antimicrobials}{A vector specifying the antimicrobials to include in the antibiogram (see \emph{Examples}). Will be evaluated using \code{\link[=guess_ab_col]{guess_ab_col()}}. This can be:
|
||||
\item{antimicrobials}{A vector specifying the antimicrobials containing SIR values to include in the antibiogram (see \emph{Examples}). Will be evaluated using \code{\link[=guess_ab_col]{guess_ab_col()}}. This can be:
|
||||
\itemize{
|
||||
\item Any antimicrobial name or code that matches to a column name in \code{x}
|
||||
\item A column name in \code{x} that contains SIR values
|
||||
\item Any antimicrobial name or code that could match (see \code{\link[=guess_ab_col]{guess_ab_col()}}) to any column in \code{x}
|
||||
\item Any \link[=antimicrobial_selectors]{antimicrobial selector}, such as \code{\link[=aminoglycosides]{aminoglycosides()}} or \code{\link[=carbapenems]{carbapenems()}}
|
||||
\item A combination of the above, using \code{c()}, e.g.:
|
||||
\itemize{
|
||||
@ -3461,7 +3460,7 @@ sir_interpretation_history(clean = FALSE)
|
||||
|
||||
\item{ab}{A vector (or column name) with \link{character}s that can be coerced to a valid antimicrobial drug code with \code{\link[=as.ab]{as.ab()}}.}
|
||||
|
||||
\item{guideline}{Defaults to EUCAST 2024 (the latest implemented EUCAST guideline in the \link{clinical_breakpoints} data set), but can be set with the package option \code{\link[=AMR-options]{AMR_guideline}}. Currently supports EUCAST (2011-2024) and CLSI (2011-2024), see \emph{Details}.}
|
||||
\item{guideline}{A guideline name (or column name) to use for SIR interpretation. Defaults to EUCAST 2024 (the latest implemented EUCAST guideline in the \link{clinical_breakpoints} data set), but can be set with the package option \code{\link[=AMR-options]{AMR_guideline}}. Currently supports EUCAST (2011-2024) and CLSI (2011-2024), see \emph{Details}. Using a column name for \code{\link[=as.sir]{as.sir()}} allows for easy interpretation on historical data which needs to be interpreted according to e.g., various years.}
|
||||
|
||||
\item{uti}{(Urinary Tract Infection) a vector (or column name) with \link{logical}s (\code{TRUE} or \code{FALSE}) to specify whether a UTI specific interpretation from the guideline should be chosen. For using \code{\link[=as.sir]{as.sir()}} on a \link{data.frame}, this can also be a column containing \link{logical}s or when left blank, the data set will be searched for a column 'specimen', and rows within this column containing 'urin' (such as 'urine', 'urina') will be regarded isolates from a UTI. See \emph{Examples}.}
|
||||
|
||||
@ -3646,7 +3645,8 @@ df_long <- data.frame(
|
||||
bacteria = rep("Escherichia coli", 4),
|
||||
antibiotic = c("amoxicillin", "cipro", "tobra", "genta"),
|
||||
mics = as.mic(c(0.01, 1, 4, 8)),
|
||||
disks = as.disk(c(6, 10, 14, 18))
|
||||
disks = as.disk(c(6, 10, 14, 18)),
|
||||
guideline = c("EUCAST 2021", "EUCAST 2022", "EUCAST 2023", "EUCAST 2024")
|
||||
)
|
||||
|
||||
\donttest{
|
||||
@ -3665,7 +3665,7 @@ if (require("dplyr")) {
|
||||
mutate_if(is.mic, as.sir,
|
||||
mo = "bacteria",
|
||||
ab = "antibiotic",
|
||||
guideline = "CLSI"
|
||||
guideline = guideline
|
||||
)
|
||||
df_long \%>\%
|
||||
mutate(across(
|
||||
@ -46,10 +46,9 @@ retrieve_wisca_parameters(wisca_model, ...)
|
||||
\arguments{
|
||||
\item{x}{A \link{data.frame} containing at least a column with microorganisms and columns with antimicrobial results (class 'sir', see \code{\link[=as.sir]{as.sir()}}).}
|
||||
|
||||
\item{antimicrobials}{A vector specifying the antimicrobials to include in the antibiogram (see \emph{Examples}). Will be evaluated using \code{\link[=guess_ab_col]{guess_ab_col()}}. This can be:
|
||||
\item{antimicrobials}{A vector specifying the antimicrobials containing SIR values to include in the antibiogram (see \emph{Examples}). Will be evaluated using \code{\link[=guess_ab_col]{guess_ab_col()}}. This can be:
|
||||
\itemize{
|
||||
\item Any antimicrobial name or code that matches to a column name in \code{x}
|
||||
\item A column name in \code{x} that contains SIR values
|
||||
\item Any antimicrobial name or code that could match (see \code{\link[=guess_ab_col]{guess_ab_col()}}) to any column in \code{x}
|
||||
\item Any \link[=antimicrobial_selectors]{antimicrobial selector}, such as \code{\link[=aminoglycosides]{aminoglycosides()}} or \code{\link[=carbapenems]{carbapenems()}}
|
||||
\item A combination of the above, using \code{c()}, e.g.:
|
||||
\itemize{
|
||||
|
||||
@ -84,7 +84,7 @@ sir_interpretation_history(clean = FALSE)
|
||||
|
||||
\item{ab}{A vector (or column name) with \link{character}s that can be coerced to a valid antimicrobial drug code with \code{\link[=as.ab]{as.ab()}}.}
|
||||
|
||||
\item{guideline}{Defaults to EUCAST 2024 (the latest implemented EUCAST guideline in the \link{clinical_breakpoints} data set), but can be set with the package option \code{\link[=AMR-options]{AMR_guideline}}. Currently supports EUCAST (2011-2024) and CLSI (2011-2024), see \emph{Details}.}
|
||||
\item{guideline}{A guideline name (or column name) to use for SIR interpretation. Defaults to EUCAST 2024 (the latest implemented EUCAST guideline in the \link{clinical_breakpoints} data set), but can be set with the package option \code{\link[=AMR-options]{AMR_guideline}}. Currently supports EUCAST (2011-2024) and CLSI (2011-2024), see \emph{Details}. Using a column name for \code{\link[=as.sir]{as.sir()}} allows for easy interpretation on historical data which needs to be interpreted according to e.g., various years.}
|
||||
|
||||
\item{uti}{(Urinary Tract Infection) a vector (or column name) with \link{logical}s (\code{TRUE} or \code{FALSE}) to specify whether a UTI specific interpretation from the guideline should be chosen. For using \code{\link[=as.sir]{as.sir()}} on a \link{data.frame}, this can also be a column containing \link{logical}s or when left blank, the data set will be searched for a column 'specimen', and rows within this column containing 'urin' (such as 'urine', 'urina') will be regarded isolates from a UTI. See \emph{Examples}.}
|
||||
|
||||
@ -269,7 +269,8 @@ df_long <- data.frame(
|
||||
bacteria = rep("Escherichia coli", 4),
|
||||
antibiotic = c("amoxicillin", "cipro", "tobra", "genta"),
|
||||
mics = as.mic(c(0.01, 1, 4, 8)),
|
||||
disks = as.disk(c(6, 10, 14, 18))
|
||||
disks = as.disk(c(6, 10, 14, 18)),
|
||||
guideline = c("EUCAST 2021", "EUCAST 2022", "EUCAST 2023", "EUCAST 2024")
|
||||
)
|
||||
|
||||
\donttest{
|
||||
@ -288,7 +289,7 @@ if (require("dplyr")) {
|
||||
mutate_if(is.mic, as.sir,
|
||||
mo = "bacteria",
|
||||
ab = "antibiotic",
|
||||
guideline = "CLSI"
|
||||
guideline = guideline
|
||||
)
|
||||
df_long \%>\%
|
||||
mutate(across(
|
||||
|
||||
@ -126,6 +126,12 @@ test_that("test-sir.R", {
|
||||
|
||||
# Human -------------------------------------------------------------------
|
||||
|
||||
# allow for guideline length > 1
|
||||
expect_equal(
|
||||
get_guideline(c("CLSI", "CLSI", "CLSI2023", "EUCAST", "EUCAST2020"), AMR::clinical_breakpoints),
|
||||
c("CLSI 2024", "CLSI 2024", "CLSI 2023", "EUCAST 2024", "EUCAST 2020")
|
||||
)
|
||||
|
||||
# these are used in the script
|
||||
expect_true(all(c("B_GRAMN", "B_GRAMP", "B_ANAER-NEG", "B_ANAER-POS", "B_ANAER") %in% AMR::microorganisms$mo))
|
||||
|
||||
@ -341,6 +347,12 @@ test_that("test-sir.R", {
|
||||
|
||||
# Veterinary --------------------------------------------------------------
|
||||
|
||||
# multiple guidelines
|
||||
sir_history <- sir_interpretation_history(clean = TRUE)
|
||||
x <- as.sir(as.mic(c(16, 16)), mo = "B_STRPT_CANS", ab = "AMK", host = "dog", guideline = c("CLSI 2024", "CLSI 2014"))
|
||||
expect_equal(x, as.sir(c("R", NA)))
|
||||
sir_history <- sir_interpretation_history(clean = TRUE)
|
||||
expect_equal(sir_history$guideline, c("CLSI 2024", "CLSI 2014"))
|
||||
sir_history <- sir_interpretation_history(clean = TRUE)
|
||||
|
||||
mics <- as.mic(2^c(-4:6)) # 0.0625 to 64 in factors of 2
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user