(v1.7.1.9054) mdro() update - fixes #49, first_isolate() speedup

v1.8.2
parent 9a2c431e16
commit 694cf5ba77
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      DESCRIPTION
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      NAMESPACE
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      NEWS.md
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@ -1,6 +1,6 @@
Package: AMR
Version: 1.7.1.9053
Date: 2021-11-01
Version: 1.7.1.9054
Date: 2021-11-28
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
@ -10,8 +10,12 @@ Authors@R: c(
person(given = c("Matthijs", "S."),
family = "Berends",
email = "m.s.berends@umcg.nl",
role = c("aut", "cre"),
role = c("aut", "cre"),
comment = c(ORCID = "0000-0001-7620-1800")),
person(given = c("Christian", "F."),
family = "Luz",
role = c("aut", "ctb"),
comment = c(ORCID = "0000-0001-5809-5995")),
person(given = "Dennis",
family = "Souverein",
role = c("aut", "ctb"),
@ -19,10 +23,6 @@ Authors@R: c(
person(given = c("Erwin", "E.", "A."),
family = "Hassing",
role = c("aut", "ctb")),
person(given = c("Christian", "F."),
family = "Luz",
role = c("aut", "ctb"),
comment = c(ORCID = "0000-0001-5809-5995")),
person(given = c("Casper", "J."),
family = "Albers",
role = "ths",
@ -30,7 +30,7 @@ Authors@R: c(
person(given = c("Judith", "M."),
family = "Fonville",
role = "ctb"),
person(given = c("Alexander", "W."),
person(given = c("Alex", "W."),
family = "Friedrich",
role = "ths",
comment = c(ORCID = "0000-0003-4881-038X")),

@ -157,6 +157,9 @@ export("%like%")
export("%like_case%")
export("%unlike%")
export("%unlike_case%")
export(NA_disk_)
export(NA_mic_)
export(NA_rsi_)
export(ab_atc)
export(ab_atc_group1)
export(ab_atc_group2)

@ -1,5 +1,5 @@
# `AMR` 1.7.1.9053
## <small>Last updated: 1 November 2021</small>
# `AMR` 1.7.1.9054
## <small>Last updated: 28 November 2021</small>
### Breaking changes
* Removed `p_symbol()` and all `filter_*()` functions (except for `filter_first_isolate()`), which were all deprecated in a previous package version
@ -7,6 +7,7 @@
* Removed all previously implemented `ggplot2::ggplot()` generics for classes `<mic>`, `<disk>`, `<rsi>` and `<resistance_predict>` as they did not follow the `ggplot2` logic. They were replaced with `ggplot2::autoplot()` generics.
### New
* Support for EUCAST Intrinsic Resistance and Unusual Phenotypes v3.3 (October 2021), effective in the `eucast_rules()` function. This is now the default guideline (all other guidelines are still available).
* Function `set_ab_names()` to rename data set columns that resemble antimicrobial drugs. This allows for quickly renaming columns to official names, ATC codes, etc.
* Support for Danish, and also added missing translations of all antimicrobial drugs in Italian, French and Portuguese
@ -34,12 +35,14 @@
* Fix for using selectors multiple times in one call (e.g., using them in `dplyr::filter()` and immediately after in `dplyr::select()`)
* Added argument `only_treatable`, which defaults to `TRUE` and will exclude drugs that are only for laboratory tests and not for treating patients (such as imipenem/EDTA and gentamicin-high)
* Fixed the Gram stain (`mo_gramstain()`) determination of the taxonomic class Negativicutes within the phylum of Firmicutes - they were considered Gram-positives because of their phylum but are actually Gram-negative. This impacts 137 taxonomic species, genera and families, such as *Negativicoccus* and *Veillonella*.
* Dramatic speed improvement for `first_isolate()`
* Fix to prevent introducing `NA`s for old MO codes when running `as.mo()` on them
* Added more informative error messages when any of the `proportion_*()` and `count_*()` functions fail
* When printing a tibble with any old MO code, a warning will be thrown that old codes should be updated using `as.mo()`
* Improved automatic column selector when `col_*` arguments are left blank, e.g. in `first_isolate()`
* The right input types for `random_mic()`, `random_disk()` and `random_rsi()` are now enforced
* `as.rsi()` can now correct for textual input (such as "Susceptible", "Resistant") in Danish, Dutch, English, French, German, Italian, Portuguese and Spanish
* `as.rsi()` has an improved algorithm and can now also correct for textual input (such as "Susceptible", "Resistant") in Danish, Dutch, English, French, German, Italian, Portuguese and Spanish
* `as.mic()` has an improved algorithm
* When warnings are thrown because of too few isolates in any `count_*()`, `proportion_*()` function (or `resistant()` or `susceptible()`), the `dplyr` group will be shown, if available
* Fix for legends created with `scale_rsi_colours()` when using `ggplot2` v3.3.4 or higher (this is ggplot2 bug 4511, soon to be fixed)
* Fix for minor translation errors
@ -48,9 +51,12 @@
* Improved plot legends for MICs and disk diffusion values
* Improved speed of `as.ab()` and all `ab_*()` functions
* Added `fortify()` extensions for plotting methods
* `NA` values of the classes `<mic>`, `<disk>` and `<rsi>` are now exported objects of this package, e.g. `NA_mic_` is an `NA` of class `mic` (just like the base R `NA_character_` is an `NA` of class `character`)
* The `proportion_df()`, `count_df()` and `rsi_df()` functions now return with the additional S3 class 'rsi_df' so they can be extended by other packages
* The `mdro()` function now returns `NA` for all rows that have no test results
### Other
* This package is now being maintained by two epidemiologists and a data scientist from two different non-profit healthcare organisations. All functions in this package are now all considered to be stable. Updates to the AMR interpretation rules (such as by EUCAST and CLSI), the microbial taxonomy, and the antibiotic dosages will all be updated yearly from now on.
* This package is now being maintained by two epidemiologists and a data scientist from two different non-profit healthcare organisations. All functions in this package are now all considered to be stable. Updates to the AMR interpretation rules (such as by EUCAST and CLSI), the microbial taxonomy, and the antibiotic dosages will all be updated every 6 to 12 months from now on.
# AMR 1.7.1

@ -119,6 +119,8 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
x <- iconv(x, from = "UTF-8", to = "ASCII//TRANSLIT")
x <- gsub('"', "", x, fixed = TRUE)
x <- gsub("(specimen|specimen date|specimen_date|spec_date|gender|^dates?$)", "", x, ignore.case = TRUE, perl = TRUE)
# penicillin is a special case: we call it so, but then mean benzylpenicillin
x[x %like_case% "^PENICILLIN" & x %unlike_case% "[ /+-]"] <- "benzylpenicillin"
x_bak_clean <- x
if (already_regex == FALSE) {
x_bak_clean <- generalise_antibiotic_name(x_bak_clean)
@ -227,6 +229,7 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
}
x_spelling <- x[i]
if (already_regex == FALSE) {
x_spelling <- gsub("[IY]+", "[IY]+", x_spelling, perl = TRUE)
x_spelling <- gsub("(C|K|Q|QU|S|Z|X|KS)+", "(C|K|Q|QU|S|Z|X|KS)+", x_spelling, perl = TRUE)
x_spelling <- gsub("(PH|F|V)+", "(PH|F|V)+", x_spelling, perl = TRUE)

@ -26,7 +26,7 @@
#' Define Custom EUCAST Rules
#'
#' Define custom EUCAST rules for your organisation or specific analysis and use the output of this function in [eucast_rules()].
#' @inheritSection lifecycle Maturing Lifecycle
#' @inheritSection lifecycle Stable Lifecycle
#' @param ... rules in formula notation, see *Examples*
#' @details
#' Some organisations have their own adoption of EUCAST rules. This function can be used to define custom EUCAST rules to be used in the [eucast_rules()] function.

@ -119,6 +119,12 @@ all_valid_disks <- function(x) {
!any(is.na(x_disk)) && !all(is.na(x))
}
#' @rdname as.disk
#' @details `NA_disk_` is a missing value of the new `<disk>` class.
#' @export
NA_disk_ <- set_clean_class(as.integer(NA_real_),
new_class = c("disk", "integer"))
#' @rdname as.disk
#' @export
is.disk <- function(x) {

@ -108,8 +108,8 @@ get_episode <- function(x, episode_days, ...) {
meet_criteria(x, allow_class = c("Date", "POSIXt"))
meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = FALSE)
exec_episode(type = "sequential",
x = x,
exec_episode(x = x,
type = "sequential",
episode_days = episode_days,
... = ...)
}
@ -120,13 +120,13 @@ is_new_episode <- function(x, episode_days, ...) {
meet_criteria(x, allow_class = c("Date", "POSIXt"))
meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = FALSE)
exec_episode(type = "logical",
x = x,
exec_episode(x = x,
type = "logical",
episode_days = episode_days,
... = ...)
}
exec_episode <- function(type, x, episode_days, ...) {
exec_episode <- function(x, type, episode_days, ...) {
x <- as.double(as.POSIXct(x)) # as.POSIXct() required for Date classes
# since x is now in seconds, get seconds from episode_days as well
episode_seconds <- episode_days * 60 * 60 * 24
@ -155,7 +155,7 @@ exec_episode <- function(type, x, episode_days, ...) {
# I asked on StackOverflow:
# https://stackoverflow.com/questions/42122245/filter-one-row-every-year
exec <- function(x, episode_seconds) {
run_episodes <- function(x, episode_seconds) {
indices <- integer()
start <- x[1]
ind <- 1
@ -181,11 +181,6 @@ exec_episode <- function(type, x, episode_days, ...) {
}
}
df <- data.frame(x = x,
y = seq_len(length(x))) %pm>%
pm_arrange(x)
df$new <- exec(df$x, episode_seconds)
df %pm>%
pm_arrange(y) %pm>%
pm_pull(new)
ord <- order(x)
run_episodes(x[ord], episode_seconds)[ord]
}

@ -23,6 +23,10 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
# ====================================================== #
# || Change the EUCAST version numbers in R/globals.R || #
# ====================================================== #
format_eucast_version_nr <- function(version, markdown = TRUE) {
# for documentation - adds title, version number, year and url in markdown language
lst <- c(EUCAST_VERSION_BREAKPOINTS, EUCAST_VERSION_EXPERT_RULES)
@ -105,6 +109,7 @@ format_eucast_version_nr <- function(version, markdown = TRUE) {
#' Leclercq et al. **EUCAST expert rules in antimicrobial susceptibility testing.** *Clin Microbiol Infect.* 2013;19(2):141-60; \doi{https://doi.org/10.1111/j.1469-0691.2011.03703.x}
#' - EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes Tables. Version 3.1, 2016. [(link)](https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf)
#' - 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 Intrinsic Resistance and Unusual Phenotypes. Version 3.3, 2021. [(link)](https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/2021/Intrinsic_Resistance_and_Unusual_Phenotypes_Tables_v3.3_20211018.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)
@ -159,7 +164,7 @@ eucast_rules <- function(x,
rules = getOption("AMR_eucastrules", default = c("breakpoints", "expert")),
verbose = FALSE,
version_breakpoints = 11.0,
version_expertrules = 3.2,
version_expertrules = 3.3,
ampc_cephalosporin_resistance = NA,
only_rsi_columns = FALSE,
custom_rules = NULL,
@ -316,25 +321,6 @@ eucast_rules <- function(x,
}
# Some helper functions ---------------------------------------------------
get_antibiotic_columns <- function(x, cols_ab) {
x <- trimws(unique(toupper(unlist(strsplit(x, ",")))))
x_new <- character()
for (val in x) {
if (paste0("AB_", val) %in% ls(envir = asNamespace("AMR"))) {
# antibiotic group names, as defined in data-raw/_internals.R, such as `AB_CARBAPENEMS`
val <- eval(parse(text = paste0("AB_", val)), envir = asNamespace("AMR"))
} else if (val %in% AB_lookup$ab) {
# separate drugs, such as `AMX`
val <- as.ab(val)
} else {
stop_("unknown antimicrobial agent (group) in EUCAST rules file: ", val, call = FALSE)
}
x_new <- c(x_new, val)
}
x_new <- unique(x_new)
out <- cols_ab[match(x_new, names(cols_ab))]
out[!is.na(out)]
}
get_antibiotic_names <- function(x) {
x <- x %pm>%
strsplit(",") %pm>%
@ -580,6 +566,7 @@ eucast_rules <- function(x,
(reference.rule_group %like% "expert" & reference.version == version_expertrules))
}
# filter out AmpC de-repressed cephalosporin-resistant mutants ----
# no need to filter on version number here - the rules contain these version number, so are inherently filtered
# cefotaxime, ceftriaxone, ceftazidime
if (is.null(ampc_cephalosporin_resistance) || isFALSE(ampc_cephalosporin_resistance)) {
eucast_rules_df <- subset(eucast_rules_df,
@ -720,7 +707,7 @@ eucast_rules <- function(x,
rows <- tryCatch(which(x[, if_mo_property, drop = TRUE] %like% mo_value),
error = function(e) integer(0))
} else {
source_antibiotics <- get_antibiotic_columns(source_antibiotics, cols_ab)
source_antibiotics <- get_ab_from_namespace(source_antibiotics, cols_ab)
if (length(source_value) == 1 & length(source_antibiotics) > 1) {
source_value <- rep(source_value, length(source_antibiotics))
}
@ -748,7 +735,7 @@ eucast_rules <- function(x,
}
}
cols <- get_antibiotic_columns(target_antibiotics, cols_ab)
cols <- get_ab_from_namespace(target_antibiotics, cols_ab)
# Apply rule on data ------------------------------------------------------
# this will return the unique number of changes

@ -238,7 +238,7 @@ first_isolate <- function(x = NULL,
meet_criteria(testcodes_exclude, allow_class = "character", allow_NULL = TRUE)
meet_criteria(icu_exclude, allow_class = "logical", has_length = 1)
meet_criteria(specimen_group, allow_class = "character", has_length = 1, allow_NULL = TRUE)
meet_criteria(type, allow_class = "character", has_length = 1)
meet_criteria(type, allow_class = "character", has_length = 1, is_in = c("points", "keyantimicrobials"))
meet_criteria(ignore_I, allow_class = "logical", has_length = 1)
meet_criteria(points_threshold, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
meet_criteria(info, allow_class = "logical", has_length = 1)
@ -250,7 +250,8 @@ first_isolate <- function(x = NULL,
any_col_contains_rsi <- any(vapply(FUN.VALUE = logical(1),
X = x,
FUN = function(x) any(as.character(x) %in% c("R", "S", "I"), na.rm = TRUE),
# check only first 10,000 rows
FUN = function(x) any(as.character(x[1:10000]) %in% c("R", "S", "I"), na.rm = TRUE),
USE.NAMES = FALSE))
if (method == "phenotype-based" & !any_col_contains_rsi) {
method <- "episode-based"
@ -443,17 +444,6 @@ first_isolate <- function(x = NULL,
!is.na(x$newvar_mo)), , drop = FALSE])
# Analysis of first isolate ----
x$other_pat_or_mo <- ifelse(x$newvar_patient_id == pm_lag(x$newvar_patient_id) &
x$newvar_genus_species == pm_lag(x$newvar_genus_species),
FALSE,
TRUE)
x$episode_group <- paste(x$newvar_patient_id, x$newvar_genus_species)
x$more_than_episode_ago <- unlist(lapply(split(x$newvar_date,
x$episode_group),
is_new_episode,
episode_days = episode_days),
use.names = FALSE)
if (!is.null(col_keyantimicrobials)) {
if (info == TRUE & message_not_thrown_before("first_isolate.type")) {
if (type == "keyantimicrobials") {
@ -470,23 +460,38 @@ first_isolate <- function(x = NULL,
as_note = FALSE)
}
}
type_param <- type
}
x$other_pat_or_mo <- ifelse(x$newvar_patient_id == pm_lag(x$newvar_patient_id) &
x$newvar_genus_species == pm_lag(x$newvar_genus_species),
FALSE,
TRUE)
x$episode_group <- paste(x$newvar_patient_id, x$newvar_genus_species)
x$more_than_episode_ago <- unlist(lapply(split(x$newvar_date,
x$episode_group),
exec_episode, # this will skip meet_criteria() in is_new_episode(), saving time
type = "logical",
episode_days = episode_days),
use.names = FALSE)
if (!is.null(col_keyantimicrobials)) {
# with key antibiotics
x$other_key_ab <- !antimicrobials_equal(y = x$newvar_key_ab,
z = pm_lag(x$newvar_key_ab),
type = type_param,
type = type,
ignore_I = ignore_I,
points_threshold = points_threshold)
# with key antibiotics
x$newvar_first_isolate <- pm_if_else(x$newvar_row_index_sorted >= row.start &
x$newvar_row_index_sorted <= row.end &
x$newvar_genus_species != "" &
(x$other_pat_or_mo | x$more_than_episode_ago | x$other_key_ab),
TRUE,
FALSE)
} else {
# no key antibiotics
x1 <<- x$other_pat_or_mo
x2 <<- x$more_than_episode_ago
x$newvar_first_isolate <- pm_if_else(x$newvar_row_index_sorted >= row.start &
x$newvar_row_index_sorted <= row.end &
x$newvar_genus_species != "" &
@ -566,7 +571,7 @@ first_isolate <- function(x = NULL,
}
# arrange back according to original sorting again
x <- x[order(x$newvar_row_index), ]
x <- x[order(x$newvar_row_index), , drop = FALSE]
rownames(x) <- NULL
if (info == TRUE) {

@ -40,6 +40,10 @@ EUCAST_VERSION_EXPERT_RULES <- list("3.1" = list(version_txt = "v3.1",
"3.2" = list(version_txt = "v3.2",
year = 2020,
title = "'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes'",
url = "https://www.eucast.org/expert_rules_and_intrinsic_resistance/"),
"3.3" = list(version_txt = "v3.3",
year = 2021,
title = "'EUCAST Expert Rules' and 'EUCAST Intrinsic Resistance and Unusual Phenotypes'",
url = "https://www.eucast.org/expert_rules_and_intrinsic_resistance/"))
SNOMED_VERSION <- list(title = "Public Health Information Network Vocabulary Access and Distribution System (PHIN VADS)",

@ -293,6 +293,28 @@ get_column_abx <- function(x,
out
}
get_ab_from_namespace <- function(x, cols_ab) {
# cols_ab comes from get_column_abx()
x <- trimws(unique(toupper(unlist(strsplit(x, ",")))))
x_new <- character()
for (val in x) {
if (paste0("AB_", val) %in% ls(envir = asNamespace("AMR"))) {
# antibiotic group names, as defined in data-raw/_internals.R, such as `AB_CARBAPENEMS`
val <- eval(parse(text = paste0("AB_", val)), envir = asNamespace("AMR"))
} else if (val %in% AB_lookup$ab) {
# separate drugs, such as `AMX`
val <- as.ab(val)
} else {
stop_("unknown antimicrobial agent (group): ", val, call = FALSE)
}
x_new <- c(x_new, val)
}
x_new <- unique(x_new)
out <- cols_ab[match(x_new, names(cols_ab))]
out[!is.na(out)]
}
generate_warning_abs_missing <- function(missing, any = FALSE) {
missing <- paste0(missing, " (", ab_name(missing, tolower = TRUE, language = NULL), ")")
if (any == TRUE) {

@ -26,7 +26,7 @@
#' Italicise Taxonomic Families, Genera, Species, Subspecies
#'
#' According to the binomial nomenclature, the lowest four taxonomic levels (family, genus, species, subspecies) should be printed in italic. This function finds taxonomic names within strings and makes them italic.
#' @inheritSection lifecycle Maturing Lifecycle
#' @inheritSection lifecycle Stable Lifecycle
#' @param string a [character] (vector)
#' @param type type of conversion of the taxonomic names, either "markdown" or "ansi", see *Details*
#' @details

@ -250,16 +250,16 @@ generate_antimcrobials_string <- function(df) {
if (NROW(df) == 0) {
return(character(0))
}
out <- tryCatch(
tryCatch({
do.call(paste0,
lapply(as.list(df),
function(x) {
x <- toupper(as.character(x))
x[!x %in% c("R", "S", "I")] <- "."
paste(x)
})),
error = function(e) rep(strrep(".", NCOL(df)), NROW(df)))
out
}))
},
error = function(e) rep(strrep(".", NCOL(df)), NROW(df)))
}
#' @rdname key_antimicrobials
@ -279,10 +279,20 @@ antimicrobials_equal <- function(y,
stop_ifnot(length(y) == length(z), "length of `y` and `z` must be equal")
key2rsi <- function(val) {
as.double(as.rsi(gsub(".", NA_character_, unlist(strsplit(val, "")), fixed = TRUE)))
val <- strsplit(val, "")[[1L]]
val.int <- rep(NA_real_, length(val))
val.int[val == "S"] <- 1
val.int[val == "I"] <- 2
val.int[val == "R"] <- 3
val.int
}
y <- lapply(y, key2rsi)
z <- lapply(z, key2rsi)
# only run on uniques
uniq <- unique(c(y, z))
uniq_list <- lapply(uniq, key2rsi)
names(uniq_list) <- uniq
y <- uniq_list[match(y, names(uniq_list))]
z <- uniq_list[match(z, names(uniq_list))]
determine_equality <- function(a, b, type, points_threshold, ignore_I) {
if (length(a) != length(b)) {

@ -536,6 +536,13 @@ mdro <- function(x = NULL,
only_rsi_columns = only_rsi_columns,
...)
}
if (!"AMP" %in% names(cols_ab) & "AMX" %in% names(cols_ab)) {
# ampicillin column is missing, but amoxicillin is available
if (info == TRUE) {
message_("Using column '", cols_ab[names(cols_ab) == "AMX"], "' as input for ampicillin since many EUCAST rules depend on it.")
}
cols_ab <- c(cols_ab, c(AMP = unname(cols_ab[names(cols_ab) == "AMX"])))
}
# nolint start
AMC <- cols_ab["AMC"]
@ -738,7 +745,8 @@ mdro <- function(x = NULL,
x[rows, "columns_nonsusceptible"] <<- vapply(FUN.VALUE = character(1),
rows,
function(row, group_vct = cols) {
cols_nonsus <- vapply(FUN.VALUE = logical(1), x[row, group_vct, drop = FALSE],
cols_nonsus <- vapply(FUN.VALUE = logical(1),
x[row, group_vct, drop = FALSE],
function(y) y %in% search_result)
paste(sort(c(unlist(strsplit(x[row, "columns_nonsusceptible", drop = TRUE], ", ")),
names(cols_nonsus)[cols_nonsus])),
@ -752,17 +760,20 @@ mdro <- function(x = NULL,
}
x_transposed <- as.list(as.data.frame(t(x[, cols, drop = FALSE]),
stringsAsFactors = FALSE))
row_filter <- vapply(FUN.VALUE = logical(1), x_transposed, function(y) search_function(y %in% search_result, na.rm = TRUE))
row_filter <- x[which(row_filter), "row_number", drop = TRUE]
rows <- rows[rows %in% row_filter]
x[rows, "MDRO"] <<- to
x[rows, "reason"] <<- paste0(any_all,
" of the required antibiotics ",
ifelse(any_all == "any", "is", "are"),
" R",
ifelse(!isTRUE(combine_SI), " or I", ""))
rows_affected <- vapply(FUN.VALUE = logical(1),
x_transposed,
function(y) search_function(y %in% search_result, na.rm = TRUE))
rows_affected <- x[which(rows_affected), "row_number", drop = TRUE]
rows_to_change <- rows[rows %in% rows_affected]
x[rows_to_change, "MDRO"] <<- to
x[rows_to_change, "reason"] <<- paste0(any_all,
" of the required antibiotics ",
ifelse(any_all == "any", "is", "are"),
" R",
ifelse(!isTRUE(combine_SI), " or I", ""))
}
}
trans_tbl2 <- function(txt, rows, lst) {
if (info == TRUE) {
message_(txt, "...", appendLF = FALSE, as_note = FALSE)
@ -1382,16 +1393,6 @@ mdro <- function(x = NULL,
x$reason <- "PDR/MDR/XDR criteria were met"
}
if (info.bak == TRUE) {
cat(group_msg)
if (sum(!is.na(x$MDRO)) == 0) {
cat(font_bold(paste0("=> Found 0 MDROs since no isolates are covered by the guideline")))
} else {
cat(font_bold(paste0("=> Found ", sum(x$MDRO %in% c(2:5), na.rm = TRUE), " ", guideline$type, " out of ", sum(!is.na(x$MDRO)),
" isolates (", trimws(percentage(sum(x$MDRO %in% c(2:5), na.rm = TRUE) / sum(!is.na(x$MDRO)))), ")\n")))
}
}
# some more info on negative results
if (verbose == TRUE) {
if (guideline$code == "cmi2012") {
@ -1406,6 +1407,31 @@ mdro <- function(x = NULL,
}
}
if (info.bak == TRUE) {
cat(group_msg)
if (sum(!is.na(x$MDRO)) == 0) {
cat(font_bold(paste0("=> Found 0 MDROs since no isolates are covered by the guideline")))
} else {
cat(font_bold(paste0("=> Found ", sum(x$MDRO %in% c(2:5), na.rm = TRUE), " ", guideline$type, " out of ", sum(!is.na(x$MDRO)),
" isolates (", trimws(percentage(sum(x$MDRO %in% c(2:5), na.rm = TRUE) / sum(!is.na(x$MDRO)))), ")")))
}
}
# Fill in blanks ----
# for rows that have no results
x_transposed <- as.list(as.data.frame(t(x[, cols_ab, drop = FALSE]),
stringsAsFactors = FALSE))
rows_empty <- which(vapply(FUN.VALUE = logical(1),
x_transposed,
function(y) all(is.na(y))))
if (length(rows_empty) > 0) {
cat(font_italic(paste0(" (", length(rows_empty), " isolates had no test results)\n")))
x[rows_empty, "MDRO"] <- NA
x[rows_empty, "reason"] <- "none of the antibiotics have test results"
} else {
cat("\n")
}
# Results ----
if (guideline$code == "cmi2012") {
if (any(x$MDRO == -1, na.rm = TRUE)) {

@ -23,9 +23,26 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
# these are allowed MIC values and will become [factor] levels
ops <- c("<", "<=", "", ">=", ">")
valid_mic_levels <- c(c(t(vapply(FUN.VALUE = character(9), ops,
function(x) paste0(x, "0.00", 1:9)))),
unique(c(t(vapply(FUN.VALUE = character(104), ops,
function(x) paste0(x, sort(as.double(paste0("0.0",
sort(c(1:99, 125, 128, 256, 512, 625)))))))))),
unique(c(t(vapply(FUN.VALUE = character(103), ops,
function(x) paste0(x, sort(as.double(paste0("0.",
c(1:99, 125, 128, 256, 512))))))))),
c(t(vapply(FUN.VALUE = character(10), ops,
function(x) paste0(x, sort(c(1:9, 1.5)))))),
c(t(vapply(FUN.VALUE = character(45), ops,
function(x) paste0(x, c(10:98)[9:98 %% 2 == TRUE])))),
c(t(vapply(FUN.VALUE = character(15), ops,
function(x) paste0(x, sort(c(2 ^ c(7:10), 80 * c(2:12))))))))
#' Transform Input to Minimum Inhibitory Concentrations (MIC)
#'
#' This ransforms vectors to a new class [`mic`], which treats the input as decimal numbers, while maintaining operators (such as ">=") and only allowing valid MIC values known to the field of (medical) microbiology.
#' This transforms vectors to a new class [`mic`], which treats the input as decimal numbers, while maintaining operators (such as ">=") and only allowing valid MIC values known to the field of (medical) microbiology.
#' @inheritSection lifecycle Stable Lifecycle
#' @rdname as.mic
#' @param x a [character] or [numeric] vector
@ -117,6 +134,8 @@ as.mic <- function(x, na.rm = FALSE) {
# transform Unicode for >= and <=
x <- gsub("\u2264", "<=", x, fixed = TRUE)
x <- gsub("\u2265", ">=", x, fixed = TRUE)
# remove other invalid characters
x <- gsub("[^a-zA-Z0-9.><= ]+", "", x, perl = TRUE)
# remove space between operator and number ("<= 0.002" -> "<=0.002")
x <- gsub("(<|=|>) +", "\\1", x, perl = TRUE)
# transform => to >= and =< to <=
@ -141,27 +160,14 @@ as.mic <- function(x, na.rm = FALSE) {
x[x %like% "[.]"] <- gsub("0+$", "", x[x %like% "[.]"])
# never end with dot
x <- gsub("[.]$", "", x, perl = TRUE)
# force to be character
x <- as.character(x)
# trim it
x <- trimws(x)
## previously unempty values now empty - should return a warning later on
x[x.bak != "" & x == ""] <- "invalid"
# these are allowed MIC values and will become [factor] levels
ops <- c("<", "<=", "", ">=", ">")
lvls <- c(c(t(vapply(FUN.VALUE = character(9), ops, function(x) paste0(x, "0.00", 1:9)))),
unique(c(t(vapply(FUN.VALUE = character(104), ops, function(x) paste0(x, sort(as.double(paste0("0.0",
sort(c(1:99, 125, 128, 256, 512, 625)))))))))),
unique(c(t(vapply(FUN.VALUE = character(103), ops, function(x) paste0(x, sort(as.double(paste0("0.",
c(1:99, 125, 128, 256, 512))))))))),
c(t(vapply(FUN.VALUE = character(10), ops, function(x) paste0(x, sort(c(1:9, 1.5)))))),
c(t(vapply(FUN.VALUE = character(45), ops, function(x) paste0(x, c(10:98)[9:98 %% 2 == TRUE])))),
c(t(vapply(FUN.VALUE = character(15), ops, function(x) paste0(x, sort(c(2 ^ c(7:10), 80 * c(2:12))))))))
na_before <- x[is.na(x) | x == ""] %pm>% length()
x[!x %in% lvls] <- NA
x[!x %in% valid_mic_levels] <- NA
na_after <- x[is.na(x) | x == ""] %pm>% length()
if (na_before != na_after) {
@ -175,7 +181,7 @@ as.mic <- function(x, na.rm = FALSE) {
list_missing, call = FALSE)
}
set_clean_class(factor(x, levels = lvls, ordered = TRUE),
set_clean_class(factor(x, levels = valid_mic_levels, ordered = TRUE),
new_class = c("mic", "ordered", "factor"))
}
}
@ -189,6 +195,12 @@ all_valid_mics <- function(x) {
!any(is.na(x_mic)) && !all(is.na(x))
}
#' @rdname as.mic
#' @details `NA_mic_` is a missing value of the new `<mic>` class.
#' @export
NA_mic_ <- set_clean_class(factor(NA, levels = valid_mic_levels, ordered = TRUE),
new_class = c("mic", "ordered", "factor"))
#' @rdname as.mic
#' @export
is.mic <- function(x) {

@ -26,7 +26,7 @@
#' Plotting for Classes `rsi`, `mic` and `disk`
#'
#' Functions to plot classes `rsi`, `mic` and `disk`, with support for base \R and `ggplot2`.
#' @inheritSection lifecycle Maturing Lifecycle
#' @inheritSection lifecycle Stable Lifecycle
#' @inheritSection AMR Read more on Our Website!
#' @param x,object values created with [as.mic()], [as.disk()] or [as.rsi()] (or their `random_*` variants, such as [random_mic()])
#' @param mo any (vector of) text that can be coerced to a valid microorganism code with [as.mo()]

@ -188,6 +188,12 @@ as.rsi <- function(x, ...) {
UseMethod("as.rsi")
}
#' @rdname as.rsi
#' @details `NA_rsi_` is a missing value of the new `<rsi>` class.
#' @export
NA_rsi_ <- set_clean_class(factor(NA, levels = c("S", "I", "R"), ordered = TRUE),
new_class = c("rsi", "ordered", "factor"))
#' @rdname as.rsi
#' @export
is.rsi <- function(x) {
@ -257,12 +263,12 @@ as.rsi.default <- function(x, ...) {
return(x)
}
if (inherits(x, c("integer", "numeric", "double")) && all(x %in% c(1:3, NA))) {
x.bak <- x
x <- as.character(x) # this is needed to prevent the vctrs pkg from throwing an error
x.bak <- x
x <- as.character(x) # this is needed to prevent the vctrs pkg from throwing an error
if (inherits(x.bak, c("integer", "numeric", "double")) && all(x %in% c(1:3, NA))) {
# support haven package for importing e.g., from SPSS - it adds the 'labels' attribute
lbls <- attributes(x)$labels
lbls <- attributes(x.bak)$labels
if (!is.null(lbls) && all(c("R", "S", "I") %in% names(lbls)) && all(c(1:3) %in% lbls)) {
x[x.bak == 1] <- names(lbls[lbls == 1])
x[x.bak == 2] <- names(lbls[lbls == 2])
@ -278,9 +284,9 @@ as.rsi.default <- function(x, ...) {
if (all(x %unlike% "(R|S|I)", na.rm = TRUE)) {
# check if they are actually MICs or disks
if (all_valid_mics(x)) {
warning_("The input seems to be MIC values. Transform them with `as.mic()` before running `as.rsi()` to interpret them.")
warning_("The input seems to contain MIC values. You can transform them with `as.mic()` before running `as.rsi()` to interpret them.", call = FALSE)
} else if (all_valid_disks(x)) {
warning_("The input seems to be disk diffusion values. Transform them with `as.disk()` before running `as.rsi()` to interpret them.")
warning_("The input seems to contain disk diffusion values. You can transform them with `as.disk()` before running `as.rsi()` to interpret them.", call = FALSE)
}
}
@ -303,26 +309,17 @@ as.rsi.default <- function(x, ...) {
x[x %like% "([^a-z]|^)res(is(tant)?)?"] <- "R"
x[x %like% "([^a-z]|^)sus(cep(tible)?)?"] <- "S"
x[x %like% "([^a-z]|^)int(er(mediate)?)?|incr.*exp"] <- "I"
# remove all spaces
x <- gsub(" +", "", x)
# remove all MIC-like values: numbers, operators and periods
x <- gsub("[0-9.,;:<=>]+", "", x)
# remove everything between brackets, and 'high' and 'low'
x <- gsub("([(].*[)])", "", x)
x <- gsub("(high|low)", "", x, ignore.case = TRUE)
# remove other invalid characters
x <- gsub("[^rsiRSIHi]+", "", x, perl = TRUE)
# some labs now report "H" instead of "I" to not interfere with EUCAST prior to 2019
x <- gsub("H", "I", x, ignore.case = TRUE)
# disallow more than 3 characters
x[nchar(x) > 3] <- NA
# set to capitals
x <- toupper(x)
# remove all invalid characters
x <- gsub("[^RSI]+", "", x)
# in cases of "S;S" keep S, but in case of "S;I" make it NA
x <- gsub("^S+$", "S", x)
x <- gsub("^I+$", "I", x)
x <- gsub("^R+$", "R", x)
x[!x %in% c("S", "I", "R")] <- NA
x[!x %in% c("S", "I", "R")] <- NA_character_
na_after <- length(x[is.na(x) | x == ""])
if (!isFALSE(list(...)$warn)) { # so as.rsi(..., warn = FALSE) will never throw a warning

@ -344,6 +344,7 @@ rsi_calc_df <- function(type, # "proportion", "count" or "both"
}
rownames(out) <- NULL
class(out) <- c("rsi_df", class(out))
out
}

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@ -1 +1 @@
9f708801889d2eaf974c6eb85c83a8e7
f7c99b5734e4cdf37f51c55faca6ac2b

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@ -214,7 +214,7 @@
"GAT" 5379 "Gatifloxacin" "Quinolones" "c(\"J01MA16\", \"S01AE06\")" "Quinolone antibacterials" "Fluoroquinolones" "c(\"\", \"gati\")" "c(\"gatiflo\", \"gatifloxacin\", \"gatifloxacine\", \"gatifloxcin\", \"gatilox\", \"gatiquin\", \"gatispan\", \"tequin\", \"tequin and zymar\", \"zymaxid\")" 0.4 "g" 0.4 "g" "character(0)"
"GEM" 9571107 "Gemifloxacin" "Quinolones" "J01MA15" "Quinolone antibacterials" "Fluoroquinolones" "" "c(\"factiv\", \"factive\", \"gemifioxacin\", \"gemifloxacin\", \"gemifloxacine\", \"gemifloxacino\", \"gemifloxacinum\")" 0.32 "g" "character(0)"
"GEN" 3467 "Gentamicin" "Aminoglycosides" "c(\"D06AX07\", \"J01GB03\", \"S01AA11\", \"S02AA14\", \"S03AA06\")" "Aminoglycoside antibacterials" "Other aminoglycosides" "c(\"cn\", \"gen\", \"gent\", \"gm\")" "c(\"apogen\", \"centicin\", \"cidomycin\", \"garasol\", \"genoptic liquifilm\", \"genoptic s.o.p.\", \"gentacycol\", \"gentafair\", \"gentak\", \"gentamar\", \"gentamcin sulfate\", \"gentamicin\", \"gentamicina\", \"gentamicine\", \"gentamicins\", \"gentamicinum\", \"gentamycin\", \"gentamycins\", \"gentamycinum\", \"gentavet\", \"gentocin\", \"jenamicin\", \"lyramycin\", \"oksitselanim\", \"refobacin\", \"refobacin tm\", \"septigen\", \"uromycine\")" 0.24 "g" "c(\"13561-6\", \"13562-4\", \"15106-8\", \"22746-2\", \"22747-0\", \"31091-2\", \"31092-0\", \"31093-8\", \"35668-3\", \"3663-2\", \"3664-0\", \"3665-7\", \"39082-3\", \"47109-4\", \"59379-8\", \"80971-5\", \"88111-0\")"
"GEH" "Gentamicin-high" "Aminoglycosides" "c(\"g_h\", \"gehl\", \"genta high\", \"gentamicin high\")" "" ""
"GEH" "Gentamicin-high" "Aminoglycosides" "c(\"gehi\", \"gehl\", \"genta high\", \"gentamicin high\")" "" ""
"GEP" 25101874 "Gepotidacin" "Other antibacterials" "" "gepotidacin" "character(0)"
"GRX" 72474 "Grepafloxacin" "Quinolones" "J01MA11" "Quinolone antibacterials" "Fluoroquinolones" "c(\"\", \"grep\")" "grepafloxacin" 0.4 "g" "character(0)"
"GRI" 441140 "Griseofulvin" "Antifungals/antimycotics" "c(\"D01AA08\", \"D01BA01\")" "" "c(\"amudane\", \"curling factor\", \"delmofulvina\", \"fulcin\", \"fulcine\", \"fulvican grisactin\", \"fulvicin\", \"fulvicin bolus\", \"fulvidex\", \"fulvina\", \"fulvinil\", \"fulvistatin\", \"fungivin\", \"greosin\", \"gresfeed\", \"gricin\", \"grifulin\", \"grifulvin\", \"grifulvin v\", \"grisactin\", \"grisactin ultra\", \"grisactin v\", \"griscofulvin\", \"grise ostatin\", \"grisefuline\", \"griseo\", \"griseofulvin\", \"griseofulvin forte\", \"griseofulvina\", \"griseofulvine\", \"griseofulvinum\", \"griseomix\", \"griseostatin\", \"grisetin\", \"grisofulvin\",
@ -403,7 +403,7 @@
"SPM" "Spiramycin/metronidazole" "Other antibacterials" "J01RA04" "Combinations of antibacterials" "Combinations of antibacterials" "" "" ""
"STR" "Streptoduocin" "Aminoglycosides" "J01GA02" "Aminoglycoside antibacterials" "Streptomycins" "" "" 1 "g" ""
"STR1" 19649 "Streptomycin" "Aminoglycosides" "c(\"A07AA04\", \"J01GA01\")" "Aminoglycoside antibacterials" "Streptomycins" "c(\"s\", \"stm\", \"str\", \"stre\")" "c(\"agrept\", \"agrimycin\", \"chemform\", \"estreptomicina\", \"neodiestreptopab\", \"strepcen\", \"streptomicina\", \"streptomycin\", \"streptomycin a\", \"streptomycin spx\", \"streptomycin sulfate\", \"streptomycine\", \"streptomyzin\", \"vetstrep\")" 1 "g" "4039-4"
"STH" "Streptomycin-high" "Aminoglycosides" "c(\"s_h\", \"sthl\", \"strepto high\", \"streptomycin high\")" "" ""
"STH" "Streptomycin-high" "Aminoglycosides" "c(\"sthi\", \"sthl\", \"strepto high\", \"streptomycin high\")" "" ""
"STI" "Streptomycin/isoniazid" "Antimycobacterials" "J04AM01" "Drugs for treatment of tuberculosis" "Combinations of drugs for treatment of tuberculosis" "" "" ""
"SUL" 130313 "Sulbactam" "Beta-lactams/penicillins" "J01CG01" "Beta-lactam antibacterials, penicillins" "Beta-lactamase inhibitors" "" "c(\"betamaze\", \"sulbactam\", \"sulbactam acid\", \"sulbactam free acid\", \"sulbactamum\")" 1 "g" "character(0)"
"SBC" 20055036 "Sulbenicillin" "Beta-lactams/penicillins" "J01CA16" "Beta-lactam antibacterials, penicillins" "Penicillins with extended spectrum" "" "c(\"kedacillina\", \"sulbenicilina\", \"sulbenicilline\", \"sulbenicillinum\")" 15 "g" "character(0)"

@ -0,0 +1,13 @@
ex2 <- example_isolates
for (extra_id in seq_len(50)) {
ex2 <- ex2 %>%
bind_rows(example_isolates %>% mutate(patient_id = paste0(patient_id, extra_id)))
}
# randomly clear antibibiograms of 2%
clr <- sort(sample(x = seq_len(nrow(ex2)),
size = nrow(ex2) * 0.02))
for (row in which(is.rsi(ex2))) {
ex2[clr, row] <- NA_rsi_
}

Binary file not shown.

@ -546,8 +546,8 @@ antibiotics[which(antibiotics$ab == "FEP"), "abbreviations"][[1]] <- list(c(anti
antibiotics[which(antibiotics$ab == "CTC"), "abbreviations"][[1]] <- list(c("xctl"))
antibiotics[which(antibiotics$ab == "CTX"), "abbreviations"][[1]] <- list(c(antibiotics[which(antibiotics$ab == "CTX"), "abbreviations"][[1]], "xct"))
# High level Gentamcin and Streptomycin
antibiotics[which(antibiotics$ab == "GEH"), "abbreviations"][[1]] <- list(c("gehl", "gentamicin high", "genta high"))
antibiotics[which(antibiotics$ab == "STH"), "abbreviations"][[1]] <- list(c("sthl", "streptomycin high", "strepto high"))
antibiotics[which(antibiotics$ab == "GEH"), "abbreviations"][[1]] <- list(c("gehl", "gentamicin high", "genta high", "gehi"))
antibiotics[which(antibiotics$ab == "STH"), "abbreviations"][[1]] <- list(c("sthl", "streptomycin high", "strepto high", "sthi"))
# add imi and "imipenem/cilastatine" to imipenem
antibiotics[which(antibiotics$ab == "IPM"), "abbreviations"][[1]] <- list(c("imip", "imi", "imp"))
antibiotics[which(antibiotics$ab == "IPM"), "synonyms"][[1]] <- list(sort(c(antibiotics[which(antibiotics$ab == "IPM"), "synonyms"][[1]], "imipenem/cilastatin")))

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@ -1,38 +1,79 @@
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