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AMR
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dr. M.S. (Matthijs) Berends 2023-01-20 11:30:40 +01:00
parent 3152f1a1ce
commit c7da8b6479
18 changed files with 323 additions and 149 deletions
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4
DESCRIPTION
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@ -1,6 +1,6 @@
Package: AMR
Version: 1.8.2.9095
Date: 2023-01-19
Version: 1.8.2.9096
Date: 2023-01-20
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

17
NAMESPACE
View File

@ -59,6 +59,10 @@ S3method(as.list,custom_eucast_rules)
S3method(as.list,custom_mdro_guideline)
S3method(as.matrix,mic)
S3method(as.numeric,mic)
S3method(as.rsi,data.frame)
S3method(as.rsi,default)
S3method(as.rsi,disk)
S3method(as.rsi,mic)
S3method(as.sir,data.frame)
S3method(as.sir,default)
S3method(as.sir,disk)
@ -173,6 +177,7 @@ export("%unlike%")
export("%unlike_case%")
export(NA_disk_)
export(NA_mic_)
export(NA_rsi_)
export(NA_sir_)
export(ab_atc)
export(ab_atc_group1)
@ -256,17 +261,21 @@ export(custom_mdro_guideline)
export(eucast_dosage)
export(eucast_exceptional_phenotypes)
export(eucast_rules)
export(facet_rsi)
export(facet_sir)
export(filter_first_isolate)
export(first_isolate)
export(fluoroquinolones)
export(full_join_microorganisms)
export(g.test)
export(geom_rsi)
export(geom_sir)
export(get_AMR_locale)
export(get_episode)
export(get_mo_source)
export(ggplot_pca)
export(ggplot_rsi)
export(ggplot_rsi_predict)
export(ggplot_sir)
export(ggplot_sir_predict)
export(glycopeptides)
@ -277,6 +286,7 @@ export(is.av)
export(is.disk)
export(is.mic)
export(is.mo)
export(is.rsi)
export(is.rsi.eligible)
export(is.sir)
export(is_new_episode)
@ -285,6 +295,7 @@ export(italicise_taxonomy)
export(italicize_taxonomy)
export(key_antimicrobials)
export(kurtosis)
export(labels_rsi_count)
export(labels_sir_count)
export(left_join_microorganisms)
export(like)
@ -335,6 +346,7 @@ export(mo_uncertainties)
export(mo_url)
export(mo_year)
export(mrgn)
export(n_rsi)
export(n_sir)
export(not_intrinsic_resistant)
export(oxazolidinones)
@ -350,11 +362,15 @@ export(proportion_df)
export(quinolones)
export(random_disk)
export(random_mic)
export(random_rsi)
export(random_sir)
export(reset_AMR_locale)
export(resistance)
export(resistance_predict)
export(right_join_microorganisms)
export(rsi_df)
export(rsi_predict)
export(scale_rsi_colours)
export(scale_sir_colours)
export(scale_y_percent)
export(semi_join_microorganisms)
@ -369,6 +385,7 @@ export(skewness)
export(streptogramins)
export(susceptibility)
export(tetracyclines)
export(theme_rsi)
export(theme_sir)
export(translate_AMR)
export(trimethoprims)

8
NEWS.md
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@ -1,4 +1,4 @@
# AMR 1.8.2.9095
# AMR 1.8.2.9096
*(this beta version will eventually become v2.0! We're happy to reach a new major milestone soon!)*
@ -6,7 +6,7 @@ This is a new major release of the AMR package, with great new additions but als
**[TL;DR](https://en.wikipedia.org/wiki/TL;DR)**
* Interpretation of SIR values is now done using `as.sir()` instead of the now deprecated `as.sir()`
* All functions and arguments with 'rsi' were replaced with 'sir', such as the interpretation of MIC values (now `as.sir()` instead of `as.rsi()`) - all old functions still work for now
* Microbiological taxonomy (`microorganisms` data set) updated to 2022 and now based on LPSN and GBIF
* Much increased algorithms to translate user input to valid taxonomy, e.g. by using [recent scientific work](https://doi.org/10.1099/mic.0.001269) about per-species human pathogenicity
* Clinical breakpoints added for EUCAST 2022 and CLSI 2022
@ -22,7 +22,7 @@ This is a new major release of the AMR package, with great new additions but als
For this milestone version, we replaced all mentions of RSI with SIR, to comply with what is actually being commonly used in the field of clinical microbiology when it comes to this tri-form regarding AMR.
While existing functions such as `as.sir()` and `sir_df()` still work, their replacements `as.sir()` and `sir_df()` are now the current functions for AMR data analysis. A warning will be thrown once a session to remind users about this. The data set `sir_translation` is now called `clinical_breakpoints` to better reflect its content.
While existing functions such as `as.rsi()`, `rsi_df()` and `ggplot_rsi()` still work, but their replacements `as.sir()`, `sir_df()`, `ggplot_sir()` are now the current functions for AMR data analysis. A warning will be thrown once a session to remind users about this. The data set `rsi_translation` is now called `clinical_breakpoints` to better reflect its content.
The 'RSI functions' will be removed in a future version, but not before late 2023 / early 2024.
@ -89,7 +89,7 @@ We now added extensive support for antiviral agents! For the first time, the `AM
* Function `sir_confidence_interval()` to add confidence intervals in AMR calculation. This is now also included in `sir_sf()` and `proportion_df()`.
* Function `mean_amr_distance()` to calculate the mean AMR distance. The mean AMR distance is a normalised numeric value to compare AMR test results and can help to identify similar isolates, without comparing antibiograms by hand.
* Function `sir_interpretation_history()` to view the history of previous runs of `as.sir()`. This returns a 'logbook' with the selected guideline, reference table and specific interpretation of each row in a data set on which `as.sir()` was run.
* Function `sir_interpretation_history()` to view the history of previous runs of `as.sir()` (previously `as.rsi()`). This returns a 'logbook' with the selected guideline, reference table and specific interpretation of each row in a data set on which `as.sir()` was run.
* Function `mo_current()` to get the currently valid taxonomic name of a microorganism
* Function `add_custom_antimicrobials()` to add custom antimicrobial codes and names to the `AMR` package

90
R/aa_deprecated.R
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@ -1,90 +0,0 @@
# ==================================================================== #
# TITLE #
# AMR: An R Package for Working with Antimicrobial Resistance Data #
# #
# SOURCE #
# https://github.com/msberends/AMR #
# #
# CITE AS #
# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
# (2022). AMR: An R Package for Working with Antimicrobial Resistance #
# Data. Journal of Statistical Software, 104(3), 1-31. #
# doi:10.18637/jss.v104.i03 #
# #
# Developed at the University of Groningen and the University Medical #
# Center Groningen in The Netherlands, in collaboration with many #
# colleagues from around the world, see our website. #
# #
# 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 data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Deprecated Functions
#'
#' These functions are so-called '[Deprecated]'. **They will be removed in a future release.** Using the functions will give a warning with the name of the function it has been replaced by (if there is one).
#' @keywords internal
#' @name AMR-deprecated
#' @rdname AMR-deprecated
#' @export
as.rsi <- function(...) {
deprecation_warning("as.rsi", "as.sir")
as.sir(...)
}
#' @rdname AMR-deprecated
#' @export
is.rsi.eligible <- function(...) {
deprecation_warning("is.rsi.eligible", "is_sir_eligible")
is_sir_eligible(...)
}
# NAMESPACE NALOPEN
# will be exported using s3_register() in R/zzz.R
pillar_shaft.rsi <- function(x, ...) {
out <- trimws(format(x))
if (has_colour()) {
# colours will anyway not work when has_colour() == FALSE,
# but then the indentation should also not be applied
out[is.na(x)] <- font_grey(" NA")
out[x == "S"] <- font_green_bg(" S ")
out[x == "I"] <- font_orange_bg(" I ")
out[x == "R"] <- font_red_bg(" R ")
}
create_pillar_column(out, align = "left", width = 5)
}
type_sum.rsi <- function(x, ...) {
deprecation_warning("as.rsi", "as.sir", "Transform your old 'rsi' class to the new 'sir' with `as.sir()` using e.g.:\n your_data %>% mutate_if(~inherits(.x, \"rsi\"), as.sir)")
"rsi"
}
#' @method print rsi
#' @export
#' @noRd
print.rsi <- function(x, ...) {
deprecation_warning("as.rsi", "as.sir", "Transform your old 'rsi' class to the new 'sir' with `as.sir()`")
print(x, ...)
}
deprecation_warning <- function(old, new = NULL, extra_msg = NULL) {
env <- paste0("deprecated_", old)
if (!env %in% names(AMR_env)) {
AMR_env[[paste0("deprecated_", old)]] <- 1
warning_(ifelse(is.null(new),
paste0("The `", old, "()` function is no longer in use"),
paste0("The `", old, "()` function has been replaced with `", new, "()`")),
", see `?AMR-deprecated`.",
ifelse(!is.null(extra_msg),
paste0(" ", extra_msg),
""),
"\nThis warning will be shown once per session.")
}
}

2
R/count.R
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@ -34,7 +34,7 @@
#' [count_resistant()] should be used to count resistant isolates, [count_susceptible()] should be used to count susceptible isolates.
#' @param ... one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with [as.sir()] if needed.
#' @inheritParams proportion
#' @inheritSection as.sir Interpretation of R and S/I
#' @inheritSection as.sir Interpretation of SIR
#' @details These functions are meant to count isolates. Use the [resistance()]/[susceptibility()] functions to calculate microbial resistance/susceptibility.
#'
#' The function [count_resistant()] is equal to the function [count_R()]. The function [count_susceptible()] is equal to the function [count_SI()].

4
R/mdro.R
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@ -127,7 +127,7 @@
#' ```
#'
#' The rules set (the `custom` object in this case) could be exported to a shared file location using [saveRDS()] if you collaborate with multiple users. The custom rules set could then be imported using [readRDS()].
#' @inheritSection as.sir Interpretation of R and S/I
#' @inheritSection as.sir Interpretation of SIR
#' @return
#' - CMI 2012 paper - function [mdr_cmi2012()] or [mdro()]:\cr
#' Ordered [factor] with levels `Negative` < `Multi-drug-resistant (MDR)` < `Extensively drug-resistant (XDR)` < `Pandrug-resistant (PDR)`
@ -1998,7 +1998,7 @@ run_custom_mdro_guideline <- function(df, guideline, info) {
out <- factor(out, levels = attributes(guideline)$values, ordered = TRUE)
}
columns_nonsusceptible <- as.data.frame(t(df[, as.sir(df), drop = FALSE] == "R"))
columns_nonsusceptible <- as.data.frame(t(df[, is.sir(df), drop = FALSE] == "R"))
columns_nonsusceptible <- vapply(
FUN.VALUE = character(1),
columns_nonsusceptible,

2
R/proportion.R
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@ -43,7 +43,7 @@
#' @param ab_result antibiotic results to test against, must be one of more values of "R", "S", "I"
#' @param confidence_level the confidence level for the returned confidence interval. For the calculation, the number of S or SI isolates, and R isolates are compared with the total number of available isolates with R, S, or I by using [binom.test()], i.e., the Clopper-Pearson method.
#' @param side the side of the confidence interval to return. Defaults to `"both"` for a length 2 vector, but can also be (abbreviated as) `"min"`/`"left"`/`"lower"`/`"less"` or `"max"`/`"right"`/`"higher"`/`"greater"`.
#' @inheritSection as.sir Interpretation of R and S/I
#' @inheritSection as.sir Interpretation of SIR
#' @details
#' The function [resistance()] is equal to the function [proportion_R()]. The function [susceptibility()] is equal to the function [proportion_SI()].
#'

2
R/resistance_predict.R
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@ -44,7 +44,7 @@
#' @param main title of the plot
#' @param ribbon a [logical] to indicate whether a ribbon should be shown (default) or error bars
#' @param ... arguments passed on to functions
#' @inheritSection as.sir Interpretation of R and S/I
#' @inheritSection as.sir Interpretation of SIR
#' @inheritParams first_isolate
#' @inheritParams graphics::plot
#' @details Valid options for the statistical model (argument `model`) are:

18
R/sir.R
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@ -95,15 +95,17 @@
#' The function [is.sir()] detects if the input contains class `sir`. If the input is a [data.frame], it iterates over all columns and returns a [logical] vector.
#'
#' The function [is_sir_eligible()] returns `TRUE` when a columns contains at most 5% invalid antimicrobial interpretations (not S and/or I and/or R), and `FALSE` otherwise. The threshold of 5% can be set with the `threshold` argument. If the input is a [data.frame], it iterates over all columns and returns a [logical] vector.
#' @section Interpretation of R and S/I:
#' In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories R and S/I as shown below (<https://www.eucast.org/newsiandr/>).
#' @section Interpretation of SIR:
#' In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories S, I, and R as shown below (<https://www.eucast.org/newsiandr/>):
#'
#' - **S - Susceptible, standard dosing regimen**\cr
#' A microorganism is categorised as "Susceptible, standard dosing regimen", when there is a high likelihood of therapeutic success using a standard dosing regimen of the agent.
#' - **I - Susceptible, increased exposure** *\cr
#' A microorganism is categorised as "Susceptible, Increased exposure*" when there is a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection.
#' - **R = Resistant**\cr
#' A microorganism is categorised as *Resistant* when there is a high likelihood of therapeutic failure even when there is increased exposure. Exposure is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.
#' - **S = Susceptible**\cr
#' A microorganism is categorised as *Susceptible, standard dosing regimen*, when there is a high likelihood of therapeutic success using a standard dosing regimen of the agent.
#' - **I = Susceptible, Increased exposure**\cr
#' A microorganism is categorised as *Susceptible, Increased exposure* when there is a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection.
#' A microorganism is categorised as "Resistant" when there is a high likelihood of therapeutic failure even when there is increased exposure.
#'
#' * *Exposure* is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.
#'
#' This AMR package honours this insight. Use [susceptibility()] (equal to [proportion_SI()]) to determine antimicrobial susceptibility and [count_susceptible()] (equal to [count_SI()]) to count susceptible isolates.
#' @return Ordered [factor] with new class `sir`
@ -216,7 +218,7 @@ as.sir <- function(x, ...) {
#' @rdname as.sir
#' @details `NA_sir_` is a missing value of the new `sir` class, analogous to e.g. base \R's [`NA_character_`][base::NA].
#' @export
NA_sir_ <- set_clean_class(factor(NA, levels = c("S", "I", "R"), ordered = TRUE),
NA_sir_ <- set_clean_class(factor(NA_character_, levels = c("S", "I", "R"), ordered = TRUE),
new_class = c("sir", "ordered", "factor")
)

9
R/translate.R
View File

@ -140,7 +140,11 @@ reset_AMR_locale <- function() {
#' @rdname translate
#' @export
translate_AMR <- function(x, language = get_AMR_locale()) {
translate_into_language(x, language = language)
translate_into_language(x,
language = language,
only_unknown = FALSE,
only_affect_ab_names = FALSE,
only_affect_mo_names = FALSE)
}
@ -192,6 +196,7 @@ translate_into_language <- function(from,
only_unknown = FALSE,
only_affect_ab_names = FALSE,
only_affect_mo_names = FALSE) {
# get ISO-639-1 of language
lang <- validate_language(language)
if (lang == "en") {
@ -259,7 +264,7 @@ translate_into_language <- function(from,
# a kind of left join to get all results back
out <- from_unique_translated[match(from.bak, from_unique)]
if (!identical(from.bak, out) && message_not_thrown_before("translation", entire_session = TRUE) && interactive()) {
if (!identical(from.bak, out) && get_AMR_locale() == lang && message_not_thrown_before("translation", entire_session = TRUE) && interactive()) {
message(word_wrap(
"Assuming the ", LANGUAGES_SUPPORTED_NAMES[[lang]]$exonym, " language (",
LANGUAGES_SUPPORTED_NAMES[[lang]]$endonym, ") for the AMR package. See `set_AMR_locale()` to change this or to silence this once-per-session note.",

182
R/zz_deprecated.R Executable file
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@ -0,0 +1,182 @@
# ==================================================================== #
# TITLE #
# AMR: An R Package for Working with Antimicrobial Resistance Data #
# #
# SOURCE #
# https://github.com/msberends/AMR #
# #
# CITE AS #
# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
# (2022). AMR: An R Package for Working with Antimicrobial Resistance #
# Data. Journal of Statistical Software, 104(3), 1-31. #
# doi:10.18637/jss.v104.i03 #
# #
# Developed at the University of Groningen and the University Medical #
# Center Groningen in The Netherlands, in collaboration with many #
# colleagues from around the world, see our website. #
# #
# 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 data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Deprecated Functions
#'
#' These functions are so-called '[Deprecated]'. **They will be removed in a future release.** Using the functions will give a warning with the name of the function it has been replaced by (if there is one).
#' @keywords internal
#' @name AMR-deprecated
#' @rdname AMR-deprecated
#' @export
NA_rsi_ <- set_clean_class(factor(NA_character_, levels = c("S", "I", "R"), ordered = TRUE),
new_class = c("rsi", "ordered", "factor"))
#' @rdname AMR-deprecated
#' @export
as.rsi <- function(x, ...) {
deprecation_warning("as.rsi", "as.sir")
UseMethod("as.rsi")
}
#' @noRd
#' @export
as.rsi.default <- function(...) {
as.sir.default(...)
}
#' @noRd
#' @export
as.rsi.mic <- function(...) {
as.sir.mic(...)
}
#' @noRd
#' @export
as.rsi.disk <- function(...) {
as.sir.disk(...)
}
#' @noRd
#' @export
as.rsi.data.frame <- function(...) {
as.sir.data.frame(...)
}
#' @rdname AMR-deprecated
#' @export
facet_rsi <- function(...) {
deprecation_warning("facet_rsi", "facet_sir")
facet_sir(...)
}
#' @rdname AMR-deprecated
#' @export
geom_rsi <- function(...) {
deprecation_warning("geom_rsi", "geom_sir")
geom_sir(...)
}
#' @rdname AMR-deprecated
#' @export
ggplot_rsi <- function(...) {
deprecation_warning("ggplot_rsi", "ggplot_sir")
ggplot_sir(...)
}
#' @rdname AMR-deprecated
#' @export
ggplot_rsi_predict <- function(...) {
deprecation_warning("ggplot_rsi_predict", "ggplot_sir_predict")
ggplot_sir_predict(...)
}
#' @rdname AMR-deprecated
#' @export
is.rsi <- function(x, ...) {
# this is an exception, so mutate_if(is.rsi, as.sir) can be used
if (inherits(x, "data.frame")) {
unname(vapply(FUN.VALUE = logical(1), x, is.rsi))
} else {
inherits(x, "rsi")
}
}
#' @rdname AMR-deprecated
#' @export
is.rsi.eligible <- function(...) {
deprecation_warning("is.rsi.eligible", "is_sir_eligible")
is_sir_eligible(...)
}
#' @rdname AMR-deprecated
#' @export
labels_rsi_count <- function(...) {
deprecation_warning("labels_rsi_count", "labels_sir_count")
labels_sir_count(...)
}
#' @rdname AMR-deprecated
#' @export
n_rsi <- function(...) {
deprecation_warning("n_rsi", "n_sir")
n_sir(...)
}
#' @rdname AMR-deprecated
#' @export
random_rsi <- function(...) {
deprecation_warning("random_rsi", "random_sir")
random_sir(...)
}
#' @rdname AMR-deprecated
#' @export
rsi_df <- function(...) {
deprecation_warning("rsi_df", "sir_df")
sir_df(...)
}
#' @rdname AMR-deprecated
#' @export
rsi_predict <- function(...) {
deprecation_warning("rsi_predict", "sir_predict")
sir_predict(...)
}
#' @rdname AMR-deprecated
#' @export
scale_rsi_colours <- function(...) {
deprecation_warning("scale_rsi_colours", "scale_sir_colours")
scale_sir_colours(...)
}
#' @rdname AMR-deprecated
#' @export
theme_rsi <- function(...) {
deprecation_warning("theme_rsi", "theme_sir")
theme_sir(...)
}
# will be exported using s3_register() in R/zzz.R
pillar_shaft.rsi <- pillar_shaft.sir
type_sum.rsi <- function(x, ...) {
deprecation_warning(extra_msg = "* Transform your old 'rsi' class to the new 'sir' class with `as.sir()` using e.g.:\n your_data %>% mutate_if(is.rsi, as.sir)")
paste0("rsi", font_bold(font_red("[!]")))
}
#' @method print rsi
#' @export
#' @noRd
print.rsi <- function(x, ...) {
deprecation_warning(extra_msg = "Transform your old 'rsi' class to the new 'sir' class with `as.sir()`")
cat("Class 'rsi'", font_bold(font_red("[!]\n")))
print(as.character(x), quote = FALSE)
}
deprecation_warning <- function(old = NULL, new = NULL, extra_msg = NULL) {
if (is.null(old)) {
warning_(extra_msg)
} else {
env <- paste0("deprecated_", old)
if (!env %in% names(AMR_env)) {
AMR_env[[paste0("deprecated_", old)]] <- 1
warning_(ifelse(is.null(new),
paste0("The `", old, "()` function is no longer in use"),
paste0("The `", old, "()` function has been replaced with `", new, "()`")),
", see `?AMR-deprecated`.",
ifelse(!is.null(extra_msg),
paste0(" ", extra_msg),
""),
"\nThis warning will be shown once per session.")
}
}
}

2
inst/tinytest/test-mo_property.R
View File

@ -95,7 +95,7 @@ expect_equal(mo_synonyms("Escherichia coli"), NULL)
expect_true(length(mo_synonyms("Candida albicans")) > 1)
expect_inherits(mo_synonyms(c("Candida albicans", "Escherichia coli")), "list")
expect_equal(names(mo_info("Escherichia coli")), c(
"identifier",
"mo",
"kingdom", "phylum", "class", "order",
"family", "genus", "species", "subspecies",
"status", "synonyms", "gramstain", "url", "ref",

47
man/AMR-deprecated.Rd
View File

@ -1,14 +1,57 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/aa_deprecated.R
% Please edit documentation in R/zz_deprecated.R
\docType{data}
\name{AMR-deprecated}
\alias{AMR-deprecated}
\alias{NA_rsi_}
\alias{as.rsi}
\alias{facet_rsi}
\alias{geom_rsi}
\alias{ggplot_rsi}
\alias{ggplot_rsi_predict}
\alias{is.rsi}
\alias{is.rsi.eligible}
\alias{labels_rsi_count}
\alias{n_rsi}
\alias{random_rsi}
\alias{rsi_df}
\alias{rsi_predict}
\alias{scale_rsi_colours}
\alias{theme_rsi}
\title{Deprecated Functions}
\format{
An object of class \code{rsi} (inherits from \code{ordered}, \code{factor}) of length 1.
}
\usage{
as.rsi(...)
NA_rsi_
as.rsi(x, ...)
facet_rsi(...)
geom_rsi(...)
ggplot_rsi(...)
ggplot_rsi_predict(...)
is.rsi(x, ...)
is.rsi.eligible(...)
labels_rsi_count(...)
n_rsi(...)
random_rsi(...)
rsi_df(...)
rsi_predict(...)
scale_rsi_colours(...)
theme_rsi(...)
}
\description{
These functions are so-called '\link{Deprecated}'. \strong{They will be removed in a future release.} Using the functions will give a warning with the name of the function it has been replaced by (if there is one).

17
man/as.sir.Rd
View File

@ -163,16 +163,19 @@ The function \code{\link[=is_sir_eligible]{is_sir_eligible()}} returns \code{TRU
\code{NA_sir_} is a missing value of the new \code{sir} class, analogous to e.g. base \R's \code{\link[base:NA]{NA_character_}}.
}
\section{Interpretation of R and S/I}{
\section{Interpretation of SIR}{
In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories R and S/I as shown below (\url{https://www.eucast.org/newsiandr/}).
In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories S, I, and R as shown below (\url{https://www.eucast.org/newsiandr/}):
\itemize{
\item \strong{S - Susceptible, standard dosing regimen}\cr
A microorganism is categorised as "Susceptible, standard dosing regimen", when there is a high likelihood of therapeutic success using a standard dosing regimen of the agent.
\item \strong{I - Susceptible, increased exposure} \emph{\cr
A microorganism is categorised as "Susceptible, Increased exposure}" when there is a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection.
\item \strong{R = Resistant}\cr
A microorganism is categorised as \emph{Resistant} when there is a high likelihood of therapeutic failure even when there is increased exposure. Exposure is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.
\item \strong{S = Susceptible}\cr
A microorganism is categorised as \emph{Susceptible, standard dosing regimen}, when there is a high likelihood of therapeutic success using a standard dosing regimen of the agent.
\item \strong{I = Susceptible, Increased exposure}\cr
A microorganism is categorised as \emph{Susceptible, Increased exposure} when there is a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection.
A microorganism is categorised as "Resistant" when there is a high likelihood of therapeutic failure even when there is increased exposure.
\itemize{
\item \emph{Exposure} is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.
}
}
This AMR package honours this insight. Use \code{\link[=susceptibility]{susceptibility()}} (equal to \code{\link[=proportion_SI]{proportion_SI()}}) to determine antimicrobial susceptibility and \code{\link[=count_susceptible]{count_susceptible()}} (equal to \code{\link[=count_SI]{count_SI()}}) to count susceptible isolates.

17
man/count.Rd
View File

@ -69,16 +69,19 @@ The function \code{\link[=n_sir]{n_sir()}} is an alias of \code{\link[=count_all
The function \code{\link[=count_df]{count_df()}} takes any variable from \code{data} that has an \code{\link{sir}} class (created with \code{\link[=as.sir]{as.sir()}}) and counts the number of S's, I's and R's. It also supports grouped variables. The function \code{\link[=sir_sf]{sir_sf()}} works exactly like \code{\link[=count_df]{count_df()}}, but adds the percentage of S, I and R.
}
\section{Interpretation of R and S/I}{
\section{Interpretation of SIR}{
In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories R and S/I as shown below (\url{https://www.eucast.org/newsiandr/}).
In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories S, I, and R as shown below (\url{https://www.eucast.org/newsiandr/}):
\itemize{
\item \strong{S - Susceptible, standard dosing regimen}\cr
A microorganism is categorised as "Susceptible, standard dosing regimen", when there is a high likelihood of therapeutic success using a standard dosing regimen of the agent.
\item \strong{I - Susceptible, increased exposure} \emph{\cr
A microorganism is categorised as "Susceptible, Increased exposure}" when there is a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection.
\item \strong{R = Resistant}\cr
A microorganism is categorised as \emph{Resistant} when there is a high likelihood of therapeutic failure even when there is increased exposure. Exposure is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.
\item \strong{S = Susceptible}\cr
A microorganism is categorised as \emph{Susceptible, standard dosing regimen}, when there is a high likelihood of therapeutic success using a standard dosing regimen of the agent.
\item \strong{I = Susceptible, Increased exposure}\cr
A microorganism is categorised as \emph{Susceptible, Increased exposure} when there is a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection.
A microorganism is categorised as "Resistant" when there is a high likelihood of therapeutic failure even when there is increased exposure.
\itemize{
\item \emph{Exposure} is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.
}
}
This AMR package honours this insight. Use \code{\link[=susceptibility]{susceptibility()}} (equal to \code{\link[=proportion_SI]{proportion_SI()}}) to determine antimicrobial susceptibility and \code{\link[=count_susceptible]{count_susceptible()}} (equal to \code{\link[=count_SI]{count_SI()}}) to count susceptible isolates.

17
man/mdro.Rd
View File

File diff suppressed because one or more lines are too long

17
man/proportion.Rd
View File

@ -141,16 +141,19 @@ and that, in combination therapies, for \code{only_all_tested = FALSE} applies t
Using \code{only_all_tested} has no impact when only using one antibiotic as input.
}
\section{Interpretation of R and S/I}{
\section{Interpretation of SIR}{
In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories R and S/I as shown below (\url{https://www.eucast.org/newsiandr/}).
In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories S, I, and R as shown below (\url{https://www.eucast.org/newsiandr/}):
\itemize{
\item \strong{S - Susceptible, standard dosing regimen}\cr
A microorganism is categorised as "Susceptible, standard dosing regimen", when there is a high likelihood of therapeutic success using a standard dosing regimen of the agent.
\item \strong{I - Susceptible, increased exposure} \emph{\cr
A microorganism is categorised as "Susceptible, Increased exposure}" when there is a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection.
\item \strong{R = Resistant}\cr
A microorganism is categorised as \emph{Resistant} when there is a high likelihood of therapeutic failure even when there is increased exposure. Exposure is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.
\item \strong{S = Susceptible}\cr
A microorganism is categorised as \emph{Susceptible, standard dosing regimen}, when there is a high likelihood of therapeutic success using a standard dosing regimen of the agent.
\item \strong{I = Susceptible, Increased exposure}\cr
A microorganism is categorised as \emph{Susceptible, Increased exposure} when there is a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection.
A microorganism is categorised as "Resistant" when there is a high likelihood of therapeutic failure even when there is increased exposure.
\itemize{
\item \emph{Exposure} is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.
}
}
This AMR package honours this insight. Use \code{\link[=susceptibility]{susceptibility()}} (equal to \code{\link[=proportion_SI]{proportion_SI()}}) to determine antimicrobial susceptibility and \code{\link[=count_susceptible]{count_susceptible()}} (equal to \code{\link[=count_SI]{count_SI()}}) to count susceptible isolates.

17
man/resistance_predict.Rd
View File

@ -110,16 +110,19 @@ Valid options for the statistical model (argument \code{model}) are:
\item \code{"lin"} or \code{"linear"}: a linear regression model
}
}
\section{Interpretation of R and S/I}{
\section{Interpretation of SIR}{
In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories R and S/I as shown below (\url{https://www.eucast.org/newsiandr/}).
In 2019, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) has decided to change the definitions of susceptibility testing categories S, I, and R as shown below (\url{https://www.eucast.org/newsiandr/}):
\itemize{
\item \strong{S - Susceptible, standard dosing regimen}\cr
A microorganism is categorised as "Susceptible, standard dosing regimen", when there is a high likelihood of therapeutic success using a standard dosing regimen of the agent.
\item \strong{I - Susceptible, increased exposure} \emph{\cr
A microorganism is categorised as "Susceptible, Increased exposure}" when there is a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection.
\item \strong{R = Resistant}\cr
A microorganism is categorised as \emph{Resistant} when there is a high likelihood of therapeutic failure even when there is increased exposure. Exposure is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.
\item \strong{S = Susceptible}\cr
A microorganism is categorised as \emph{Susceptible, standard dosing regimen}, when there is a high likelihood of therapeutic success using a standard dosing regimen of the agent.
\item \strong{I = Susceptible, Increased exposure}\cr
A microorganism is categorised as \emph{Susceptible, Increased exposure} when there is a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection.
A microorganism is categorised as "Resistant" when there is a high likelihood of therapeutic failure even when there is increased exposure.
\itemize{
\item \emph{Exposure} is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.
}
}
This AMR package honours this insight. Use \code{\link[=susceptibility]{susceptibility()}} (equal to \code{\link[=proportion_SI]{proportion_SI()}}) to determine antimicrobial susceptibility and \code{\link[=count_susceptible]{count_susceptible()}} (equal to \code{\link[=count_SI]{count_SI()}}) to count susceptible isolates.