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mdro.R
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mdro.R
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# ==================================================================== #
# TITLE: #
# AMR: An R Package for Working with Antimicrobial Resistance Data #
# #
# SOURCE CODE: #
# https://github.com/msberends/AMR #
# #
# PLEASE CITE THIS SOFTWARE 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. #
# https://doi.org/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/ #
# ==================================================================== #
#' Determine Multidrug-Resistant Organisms (MDRO)
#'
#' Determine which isolates are multidrug-resistant organisms (MDRO) according to international, national and custom guidelines.
#' @param x a [data.frame] with antibiotics columns, like `AMX` or `amox`. Can be left blank for automatic determination.
#' @param guideline a specific guideline to follow, see sections *Supported international / national guidelines* and *Using Custom Guidelines* below. When left empty, the publication by Magiorakos *et al.* (see below) will be followed.
#' @param ... in case of [custom_mdro_guideline()]: a set of rules, see section *Using Custom Guidelines* below. Otherwise: column name of an antibiotic, see section *Antibiotics* below.
#' @param as_factor a [logical] to indicate whether the returned value should be an ordered [factor] (`TRUE`, default), or otherwise a [character] vector
#' @inheritParams eucast_rules
#' @param pct_required_classes minimal required percentage of antimicrobial classes that must be available per isolate, rounded down. For example, with the default guideline, 17 antimicrobial classes must be available for *S. aureus*. Setting this `pct_required_classes` argument to `0.5` (default) means that for every *S. aureus* isolate at least 8 different classes must be available. Any lower number of available classes will return `NA` for that isolate.
#' @param combine_SI a [logical] to indicate whether all values of S and I must be merged into one, so resistance is only considered when isolates are R, not I. As this is the default behaviour of the [mdro()] function, it follows the redefinition by EUCAST about the interpretation of I (increased exposure) in 2019, see section 'Interpretation of S, I and R' below. When using `combine_SI = FALSE`, resistance is considered when isolates are R or I.
#' @param verbose a [logical] to turn Verbose mode on and off (default is off). In Verbose mode, the function does not return the MDRO results, but instead returns a data set in logbook form with extensive info about which isolates would be MDRO-positive, or why they are not.
#' @inheritSection eucast_rules Antibiotics
#' @details
#' These functions are context-aware. This means that the `x` argument can be left blank if used inside a [data.frame] call, see *Examples*.
#'
#' For the `pct_required_classes` argument, values above 1 will be divided by 100. This is to support both fractions (`0.75` or `3/4`) and percentages (`75`).
#'
#' **Note:** Every test that involves the Enterobacteriaceae family, will internally be performed using its newly named *order* Enterobacterales, since the Enterobacteriaceae family has been taxonomically reclassified by Adeolu *et al.* in 2016. Before that, Enterobacteriaceae was the only family under the Enterobacteriales (with an i) order. All species under the old Enterobacteriaceae family are still under the new Enterobacterales (without an i) order, but divided into multiple families. The way tests are performed now by this [mdro()] function makes sure that results from before 2016 and after 2016 are identical.
#'
#' @section Supported International / National Guidelines:
#'
#' Currently supported guidelines are (case-insensitive):
#'
#' * `guideline = "CMI2012"` (default)
#'
#' Magiorakos AP, Srinivasan A *et al.* "Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance." Clinical Microbiology and Infection (2012) (\doi{10.1111/j.1469-0691.2011.03570.x})
#'
#' * `guideline = "EUCAST3.3"` (or simply `guideline = "EUCAST"`)
#'
#' The European international guideline - EUCAST Expert Rules Version 3.3 "Intrinsic Resistance and Unusual Phenotypes" ([link](https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/2021/Intrinsic_Resistance_and_Unusual_Phenotypes_Tables_v3.3_20211018.pdf))
#'
#' * `guideline = "EUCAST3.2"`
#'
#' The European international guideline - EUCAST Expert Rules Version 3.2 "Intrinsic Resistance and Unusual Phenotypes" ([link](https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/2020/Intrinsic_Resistance_and_Unusual_Phenotypes_Tables_v3.2_20200225.pdf))
#'
#' * `guideline = "EUCAST3.1"`
#'
#' The European international guideline - EUCAST Expert Rules Version 3.1 "Intrinsic Resistance and Exceptional Phenotypes Tables" ([link](https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf))
#'
#' * `guideline = "TB"`
#'
#' The international guideline for multi-drug resistant tuberculosis - World Health Organization "Companion handbook to the WHO guidelines for the programmatic management of drug-resistant tuberculosis" ([link](https://www.who.int/publications/i/item/9789241548809))
#'
#' * `guideline = "MRGN"`
#'
#' The German national guideline - Mueller et al. (2015) Antimicrobial Resistance and Infection Control 4:7; \doi{10.1186/s13756-015-0047-6}
#'
#' * `guideline = "BRMO"`
#'
#' The Dutch national guideline - Rijksinstituut voor Volksgezondheid en Milieu "WIP-richtlijn BRMO (Bijzonder Resistente Micro-Organismen) (ZKH)" ([link](https://www.rivm.nl/wip-richtlijn-brmo-bijzonder-resistente-micro-organismen-zkh))
#'
#' Please suggest your own (country-specific) guidelines by letting us know: <https://github.com/msberends/AMR/issues/new>.
#'
#' @section Using Custom Guidelines:
#'
#' Custom guidelines can be set with the [custom_mdro_guideline()] function. This is of great importance if you have custom rules to determine MDROs in your hospital, e.g., rules that are dependent on ward, state of contact isolation or other variables in your data.
#'
#' If you are familiar with the [`case_when()`][dplyr::case_when()] function of the `dplyr` package, you will recognise the input method to set your own rules. Rules must be set using what \R considers to be the 'formula notation'. The rule is written *before* the tilde (`~`) and the consequence of the rule is written *after* the tilde:
#'
#' ```
#' custom <- custom_mdro_guideline(CIP == "R" & age > 60 ~ "Elderly Type A",
#' ERY == "R" & age > 60 ~ "Elderly Type B")
#' ```
#'
#' If a row/an isolate matches the first rule, the value after the first `~` (in this case *'Elderly Type A'*) will be set as MDRO value. Otherwise, the second rule will be tried and so on. The number of rules is unlimited.
#'
#' You can print the rules set in the console for an overview. Colours will help reading it if your console supports colours.
#'
#' ```
#' custom
#' #> A set of custom MDRO rules:
#' #> 1. CIP is "R" and age is higher than 60 -> Elderly Type A
#' #> 2. ERY is "R" and age is higher than 60 -> Elderly Type B
#' #> 3. Otherwise -> Negative
#' #>
#' #> Unmatched rows will return NA.
#' ```
#'
#' The outcome of the function can be used for the `guideline` argument in the [mdro()] function:
#'
#' ```
#' x <- mdro(example_isolates,
#' guideline = custom)
#' table(x)
#' #> Negative Elderly Type A Elderly Type B
#' #> 1070 198 732
#' ```
#'
#' Rules can also be combined with other custom rules by using [c()]:
#'
#' ```
#' x <- mdro(example_isolates,
#' guideline = c(custom,
#' custom_mdro_guideline(ERY == "R" & age > 50 ~ "Elderly Type C")))
#' table(x)
#' #> Negative Elderly Type A Elderly Type B Elderly Type C
#' #> 961 198 732 109
#' ```
#'
#' 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 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)`
#' - TB guideline - function [mdr_tb()] or [`mdro(..., guideline = "TB")`][mdro()]:\cr
#' Ordered [factor] with levels `Negative` < `Mono-resistant` < `Poly-resistant` < `Multi-drug-resistant` < `Extensively drug-resistant`
#' - German guideline - function [mrgn()] or [`mdro(..., guideline = "MRGN")`][mdro()]:\cr
#' Ordered [factor] with levels `Negative` < `3MRGN` < `4MRGN`
#' - Everything else, except for custom guidelines:\cr
#' Ordered [factor] with levels `Negative` < `Positive, unconfirmed` < `Positive`. The value `"Positive, unconfirmed"` means that, according to the guideline, it is not entirely sure if the isolate is multi-drug resistant and this should be confirmed with additional (e.g. molecular) tests
#' @rdname mdro
#' @aliases MDR XDR PDR BRMO 3MRGN 4MRGN
#' @export
#' @source
#' See the supported guidelines above for the [list] of publications used for this function.
#' @examples
#' out <- mdro(example_isolates, guideline = "EUCAST")
#' str(out)
#' table(out)
#'
#' out <- mdro(example_isolates,
#' guideline = custom_mdro_guideline(
#' AMX == "R" ~ "Custom MDRO 1",
#' VAN == "R" ~ "Custom MDRO 2"
#' )
#' )
#' table(out)
#'
#' \donttest{
#' if (require("dplyr")) {
#' example_isolates %>%
#' mdro() %>%
#' table()
#'
#' # no need to define `x` when used inside dplyr verbs:
#' example_isolates %>%
#' mutate(MDRO = mdro()) %>%
#' pull(MDRO) %>%
#' table()
#' }
#' }
mdro <- function(x = NULL,
guideline = "CMI2012",
col_mo = NULL,
info = interactive(),
pct_required_classes = 0.5,
combine_SI = TRUE,
verbose = FALSE,
only_sir_columns = FALSE,
...) {
if (is_null_or_grouped_tbl(x)) {
# when `x` is left blank, auto determine it (get_current_data() searches underlying data within call)
# is also a fix for using a grouped df as input (i.e., a dot as first argument)
x <- tryCatch(get_current_data(arg_name = "x", call = -2), error = function(e) x)
}
meet_criteria(x, allow_class = "data.frame") # also checks dimensions to be >0
meet_criteria(guideline, allow_class = c("list", "character"), allow_NULL = TRUE)
if (!is.list(guideline)) {
meet_criteria(guideline, allow_class = "character", has_length = 1, allow_NULL = TRUE)
}
meet_criteria(col_mo, allow_class = "character", has_length = 1, is_in = colnames(x), allow_NULL = TRUE)
meet_criteria(info, allow_class = "logical", has_length = 1)
meet_criteria(pct_required_classes, allow_class = "numeric", has_length = 1)
meet_criteria(combine_SI, allow_class = "logical", has_length = 1)
meet_criteria(verbose, allow_class = "logical", has_length = 1)
meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
if (!any(is_sir_eligible(x))) {
stop_("There were no possible SIR columns found in the data set. Transform columns with `as.sir()` for valid antimicrobial interpretations.")
}
info.bak <- info
# don't throw info's more than once per call
if (isTRUE(info)) {
info <- message_not_thrown_before("mdro")
}
if (interactive() && isTRUE(verbose) && isTRUE(info)) {
txt <- paste0(
"WARNING: In Verbose mode, the mdro() function does not return the MDRO results, but instead returns a data set in logbook form with extensive info about which isolates would be MDRO-positive, or why they are not.",
"\n\nThis may overwrite your existing data if you use e.g.:",
"\ndata <- mdro(data, verbose = TRUE)\n\nDo you want to continue?"
)
showQuestion <- import_fn("showQuestion", "rstudioapi", error_on_fail = FALSE)
if (!is.null(showQuestion)) {
q_continue <- showQuestion("Using verbose = TRUE with mdro()", txt)
} else {
q_continue <- utils::menu(choices = c("OK", "Cancel"), graphics = FALSE, title = txt)
}
if (q_continue %in% c(FALSE, 2)) {
message_("Cancelled, returning original data", add_fn = font_red, as_note = FALSE)
return(x)
}
}
group_msg <- ""
if (isTRUE(info.bak)) {
# print group name if used in dplyr::group_by()
cur_group <- import_fn("cur_group", "dplyr", error_on_fail = FALSE)
if (!is.null(cur_group)) {
group_df <- tryCatch(cur_group(), error = function(e) data.frame())
if (NCOL(group_df) > 0) {
# transform factors to characters
group <- vapply(FUN.VALUE = character(1), group_df, function(x) {
if (is.numeric(x)) {
format(x)
} else if (is.logical(x)) {
as.character(x)
} else {
paste0('"', x, '"')
}
})
group_msg <- paste0("\nGroup: ", paste0(names(group), " = ", group, collapse = ", "), "\n")
}
}
}
# force regular [data.frame], not a tibble or data.table
x <- as.data.frame(x, stringsAsFactors = FALSE)
if (pct_required_classes > 1) {
# allow pct_required_classes = 75 -> pct_required_classes = 0.75
pct_required_classes <- pct_required_classes / 100
}
guideline.bak <- guideline
if (is.list(guideline)) {
# Custom MDRO guideline ---------------------------------------------------
stop_ifnot(inherits(guideline, "custom_mdro_guideline"), "use `custom_mdro_guideline()` to create custom guidelines")
if (isTRUE(info)) {
txt <- paste0(
"Determining MDROs based on custom rules",
ifelse(isTRUE(attributes(guideline)$as_factor),
paste0(", resulting in factor levels: ", paste0(attributes(guideline)$values, collapse = " < ")),
""
),
"."
)
txt <- word_wrap(txt)
cat(txt, "\n", sep = "")
}
x <- run_custom_mdro_guideline(df = x, guideline = guideline, info = info)
if (isTRUE(info.bak)) {
cat(group_msg)
if (sum(!is.na(x$MDRO)) == 0) {
cat(word_wrap(font_bold(paste0("=> Found 0 MDROs since no isolates are covered by the custom guideline"))))
} else {
cat(word_wrap(font_bold(paste0(
"=> Found ", sum(x$MDRO != "Negative", na.rm = TRUE),
" custom defined MDROs out of ", sum(!is.na(x$MDRO)),
" isolates (",
trimws(percentage(sum(x$MDRO != "Negative", na.rm = TRUE) / sum(!is.na(x$MDRO)))),
")\n"
))))
}
}
if (isTRUE(verbose)) {
return(x[, c(
"row_number",
"MDRO",
"reason",
"columns_nonsusceptible"
)])
} else {
return(x$MDRO)
}
}
guideline <- tolower(gsub("[^a-zA-Z0-9.]+", "", guideline))
if (is.null(guideline)) {
# default to the paper by Magiorakos et al. (2012)
guideline <- "cmi2012"
}
if (guideline == "eucast") {
# turn into latest EUCAST guideline
guideline <- "eucast3.3"
}
if (guideline == "nl") {
guideline <- "brmo"
}
if (guideline == "de") {
guideline <- "mrgn"
}
stop_ifnot(
guideline %in% c("brmo", "mrgn", "eucast3.1", "eucast3.2", "eucast3.3", "tb", "cmi2012"),
"invalid guideline: ", guideline.bak
)
guideline <- list(code = guideline)
# try to find columns based on type
# -- mo
if (is.null(col_mo)) {
col_mo <- search_type_in_df(x = x, type = "mo", info = info)
}
if (is.null(col_mo) && guideline$code == "tb") {
message_(
"No column found as input for `col_mo`, ",
font_bold(paste0("assuming all rows contain ", font_italic("Mycobacterium tuberculosis"), "."))
)
x$mo <- as.mo("Mycobacterium tuberculosis", keep_synonyms = TRUE)
col_mo <- "mo"
}
stop_if(is.null(col_mo), "`col_mo` must be set")
if (guideline$code == "cmi2012") {
guideline$name <- "Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance."
guideline$author <- "Magiorakos AP, Srinivasan A, Carey RB, ..., Vatopoulos A, Weber JT, Monnet DL"
guideline$version <- NA
guideline$source_url <- paste0("Clinical Microbiology and Infection 18:3, 2012; ", font_url("https://doi.org/10.1111/j.1469-0691.2011.03570.x", "doi: 10.1111/j.1469-0691.2011.03570.x"))
guideline$type <- "MDRs/XDRs/PDRs"
} else if (guideline$code == "eucast3.1") {
guideline$name <- "EUCAST Expert Rules, \"Intrinsic Resistance and Exceptional Phenotypes Tables\""
guideline$author <- "EUCAST (European Committee on Antimicrobial Susceptibility Testing)"
guideline$version <- "3.1, 2016"
guideline$source_url <- font_url("https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf", "Direct download")
guideline$type <- "EUCAST Exceptional Phenotypes"
} else if (guideline$code == "eucast3.2") {
guideline$name <- "EUCAST Expert Rules, \"Intrinsic Resistance and Unusual Phenotypes\""
guideline$author <- "EUCAST (European Committee on Antimicrobial Susceptibility Testing)"
guideline$version <- "3.2, February 2020"
guideline$source_url <- font_url("https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/2020/Intrinsic_Resistance_and_Unusual_Phenotypes_Tables_v3.2_20200225.pdf", "Direct download")
guideline$type <- "EUCAST Unusual Phenotypes"
} else if (guideline$code == "eucast3.3") {
guideline$name <- "EUCAST Expert Rules, \"Intrinsic Resistance and Unusual Phenotypes\""
guideline$author <- "EUCAST (European Committee on Antimicrobial Susceptibility Testing)"
guideline$version <- "3.3, October 2021"
guideline$source_url <- font_url("https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/2021/Intrinsic_Resistance_and_Unusual_Phenotypes_Tables_v3.3_20211018.pdf", "Direct download")
guideline$type <- "EUCAST Unusual Phenotypes"
} else if (guideline$code == "tb") {
guideline$name <- "Companion handbook to the WHO guidelines for the programmatic management of drug-resistant tuberculosis"
guideline$author <- "WHO (World Health Organization)"
guideline$version <- "WHO/HTM/TB/2014.11, 2014"
guideline$source_url <- font_url("https://www.who.int/publications/i/item/9789241548809", "Direct download")
guideline$type <- "MDR-TB's"
# support per country:
} else if (guideline$code == "mrgn") {
guideline$name <- "Cross-border comparison of the Dutch and German guidelines on multidrug-resistant Gram-negative microorganisms"
guideline$author <- "M\u00fcller J, Voss A, K\u00f6ck R, ..., Kern WV, Wendt C, Friedrich AW"
guideline$version <- NA
guideline$source_url <- paste0("Antimicrobial Resistance and Infection Control 4:7, 2015; ", font_url("https://doi.org/10.1186/s13756-015-0047-6", "doi: 10.1186/s13756-015-0047-6"))
guideline$type <- "MRGNs"
} else if (guideline$code == "brmo") {
guideline$name <- "WIP-Richtlijn Bijzonder Resistente Micro-organismen (BRMO)"
guideline$author <- "RIVM (Rijksinstituut voor de Volksgezondheid)"
guideline$version <- "Revision as of December 2017"
guideline$source_url <- font_url("https://www.rivm.nl/Documenten_en_publicaties/Professioneel_Praktisch/Richtlijnen/Infectieziekten/WIP_Richtlijnen/WIP_Richtlijnen/Ziekenhuizen/WIP_richtlijn_BRMO_Bijzonder_Resistente_Micro_Organismen_ZKH", "Direct download")
guideline$type <- "BRMOs"
} else {
stop("This guideline is currently unsupported: ", guideline$code, call. = FALSE)
}
if (guideline$code == "cmi2012") {
cols_ab <- get_column_abx(
x = x,
soft_dependencies = c(
# [table] 1 (S aureus)
"GEN", "RIF", "CPT", "OXA", "CIP", "MFX", "SXT", "FUS", "VAN", "TEC", "TLV", "TGC", "CLI", "DAP", "ERY", "LNZ", "CHL", "FOS", "QDA", "TCY", "DOX", "MNO",
# [table] 2 (Enterococcus)
"GEH", "STH", "IPM", "MEM", "DOR", "CIP", "LVX", "MFX", "VAN", "TEC", "TGC", "DAP", "LNZ", "AMP", "QDA", "DOX", "MNO",
# [table] 3 (Enterobacteriaceae)
"GEN", "TOB", "AMK", "NET", "CPT", "TCC", "TZP", "ETP", "IPM", "MEM", "DOR", "CZO", "CXM", "CTX", "CAZ", "FEP", "FOX", "CTT", "CIP", "SXT", "TGC", "ATM", "AMP", "AMC", "SAM", "CHL", "FOS", "COL", "TCY", "DOX", "MNO",
# [table] 4 (Pseudomonas)
"GEN", "TOB", "AMK", "NET", "IPM", "MEM", "DOR", "CAZ", "FEP", "CIP", "LVX", "TCC", "TZP", "ATM", "FOS", "COL", "PLB",
# [table] 5 (Acinetobacter)
"GEN", "TOB", "AMK", "NET", "IPM", "MEM", "DOR", "CIP", "LVX", "TZP", "TCC", "CTX", "CRO", "CAZ", "FEP", "SXT", "SAM", "COL", "PLB", "TCY", "DOX", "MNO"
),
verbose = verbose,
info = info,
only_sir_columns = only_sir_columns,
fn = "mdro",
...
)
} else if (guideline$code == "eucast3.2") {
cols_ab <- get_column_abx(
x = x,
soft_dependencies = c("AMP", "AMX", "CIP", "DAL", "DAP", "ERV", "FDX", "GEN", "LNZ", "MEM", "MTR", "OMC", "ORI", "PEN", "QDA", "RIF", "TEC", "TGC", "TLV", "TOB", "TZD", "VAN"),
verbose = verbose,
info = info,
only_sir_columns = only_sir_columns,
fn = "mdro",
...
)
} else if (guideline$code == "eucast3.3") {
cols_ab <- get_column_abx(
x = x,
soft_dependencies = c("AMP", "AMX", "CIP", "DAL", "DAP", "ERV", "FDX", "GEN", "LNZ", "MEM", "MTR", "OMC", "ORI", "PEN", "QDA", "RIF", "TEC", "TGC", "TLV", "TOB", "TZD", "VAN"),
verbose = verbose,
info = info,
only_sir_columns = only_sir_columns,
fn = "mdro",
...
)
} else if (guideline$code == "tb") {
cols_ab <- get_column_abx(
x = x,
soft_dependencies = c("CAP", "ETH", "GAT", "INH", "PZA", "RIF", "RIB", "RFP"),
verbose = verbose,
info = info,
only_sir_columns = only_sir_columns,
fn = "mdro",
...
)
} else if (guideline$code == "mrgn") {
cols_ab <- get_column_abx(
x = x,
soft_dependencies = c("PIP", "CTX", "CAZ", "IPM", "MEM", "CIP"),
verbose = verbose,
info = info,
only_sir_columns = only_sir_columns,
fn = "mdro",
...
)
} else {
cols_ab <- get_column_abx(
x = x,
verbose = verbose,
info = info,
only_sir_columns = only_sir_columns,
fn = "mdro",
...
)
}
if (!"AMP" %in% names(cols_ab) && "AMX" %in% names(cols_ab)) {
# ampicillin column is missing, but amoxicillin is available
if (isTRUE(info)) {
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"]
AMK <- cols_ab["AMK"]
AMP <- cols_ab["AMP"]
AMX <- cols_ab["AMX"]
ATM <- cols_ab["ATM"]
AZL <- cols_ab["AZL"]
AZM <- cols_ab["AZM"]
BPR <- cols_ab["BPR"]
CAC <- cols_ab["CAC"]
CAT <- cols_ab["CAT"]
CAZ <- cols_ab["CAZ"]
CCV <- cols_ab["CCV"]
CDR <- cols_ab["CDR"]
CDZ <- cols_ab["CDZ"]
CEC <- cols_ab["CEC"]
CED <- cols_ab["CED"]
CEI <- cols_ab["CEI"]
CEP <- cols_ab["CEP"]
CFM <- cols_ab["CFM"]
CFM1 <- cols_ab["CFM1"]
CFP <- cols_ab["CFP"]
CFR <- cols_ab["CFR"]
CFS <- cols_ab["CFS"]
CHL <- cols_ab["CHL"]
CID <- cols_ab["CID"]
CIP <- cols_ab["CIP"]
CLI <- cols_ab["CLI"]
CLR <- cols_ab["CLR"]
CMX <- cols_ab["CMX"]
CMZ <- cols_ab["CMZ"]
CND <- cols_ab["CND"]
COL <- cols_ab["COL"]
CPD <- cols_ab["CPD"]
CPM <- cols_ab["CPM"]
CPO <- cols_ab["CPO"]
CPR <- cols_ab["CPR"]
CPT <- cols_ab["CPT"]
CRD <- cols_ab["CRD"]
CRO <- cols_ab["CRO"]
CSL <- cols_ab["CSL"]
CTB <- cols_ab["CTB"]
CTF <- cols_ab["CTF"]
CTL <- cols_ab["CTL"]
CTT <- cols_ab["CTT"]
CTX <- cols_ab["CTX"]
CTZ <- cols_ab["CTZ"]
CXM <- cols_ab["CXM"]
CZD <- cols_ab["CZD"]
CZO <- cols_ab["CZO"]
CZX <- cols_ab["CZX"]
DAL <- cols_ab["DAL"]
DAP <- cols_ab["DAP"]
DIT <- cols_ab["DIT"]
DIZ <- cols_ab["DIZ"]
DOR <- cols_ab["DOR"]
DOX <- cols_ab["DOX"]
ENX <- cols_ab["ENX"]
ERV <- cols_ab["ERV"]
ERY <- cols_ab["ERY"]
ETP <- cols_ab["ETP"]
FDX <- cols_ab["FDX"]
FEP <- cols_ab["FEP"]
FLC <- cols_ab["FLC"]
FLE <- cols_ab["FLE"]
FOS <- cols_ab["FOS"]
FOX <- cols_ab["FOX"]
FUS <- cols_ab["FUS"]
GAT <- cols_ab["GAT"]
GEH <- cols_ab["GEH"]
GEM <- cols_ab["GEM"]
GEN <- cols_ab["GEN"]
GRX <- cols_ab["GRX"]
HAP <- cols_ab["HAP"]
IPM <- cols_ab["IPM"]
KAN <- cols_ab["KAN"]
LEX <- cols_ab["LEX"]
LIN <- cols_ab["LIN"]
LNZ <- cols_ab["LNZ"]
LOM <- cols_ab["LOM"]
LOR <- cols_ab["LOR"]
LTM <- cols_ab["LTM"]
LVX <- cols_ab["LVX"]
MAN <- cols_ab["MAN"]
MEM <- cols_ab["MEM"]
MEV <- cols_ab["MEV"]
MEZ <- cols_ab["MEZ"]
MFX <- cols_ab["MFX"]
MNO <- cols_ab["MNO"]
MTR <- cols_ab["MTR"]
NAL <- cols_ab["NAL"]
NEO <- cols_ab["NEO"]
NET <- cols_ab["NET"]
NIT <- cols_ab["NIT"]
NOR <- cols_ab["NOR"]
NOV <- cols_ab["NOV"]
OFX <- cols_ab["OFX"]
OMC <- cols_ab["OMC"]
ORI <- cols_ab["ORI"]
OXA <- cols_ab["OXA"]
PAZ <- cols_ab["PAZ"]
PEF <- cols_ab["PEF"]
PEN <- cols_ab["PEN"]
PIP <- cols_ab["PIP"]
PLB <- cols_ab["PLB"]
PRI <- cols_ab["PRI"]
PRU <- cols_ab["PRU"]
QDA <- cols_ab["QDA"]
RFL <- cols_ab["RFL"]
RID <- cols_ab["RID"]
RIF <- cols_ab["RIF"]
RXT <- cols_ab["RXT"]
SAM <- cols_ab["SAM"]
SIS <- cols_ab["SIS"]
SPT <- cols_ab["SPT"]
SPX <- cols_ab["SPX"]
STH <- cols_ab["STH"]
SXT <- cols_ab["SXT"]
TCC <- cols_ab["TCC"]
TCY <- cols_ab["TCY"]
TEC <- cols_ab["TEC"]
TGC <- cols_ab["TGC"]
TIC <- cols_ab["TIC"]
TLV <- cols_ab["TLV"]
TMP <- cols_ab["TMP"]
TMX <- cols_ab["TMX"]
TOB <- cols_ab["TOB"]
TVA <- cols_ab["TVA"]
TZD <- cols_ab["TZD"]
TZP <- cols_ab["TZP"]
VAN <- cols_ab["VAN"]
# additional for TB
CAP <- cols_ab["CAP"]
ETH <- cols_ab["ETH"]
GAT <- cols_ab["GAT"]
INH <- cols_ab["INH"]
PZA <- cols_ab["PZA"]
RIF <- cols_ab["RIF"]
RIB <- cols_ab["RIB"]
RFP <- cols_ab["RFP"]
abx_tb <- c(CAP, ETH, GAT, INH, PZA, RIF, RIB, RFP)
abx_tb <- abx_tb[!is.na(abx_tb)]
stop_if(guideline$code == "tb" & length(abx_tb) == 0, "no antimycobacterials found in data set")
# nolint end
if (isTRUE(combine_SI)) {
search_result <- "R"
} else {
search_result <- c("R", "I")
}
if (isTRUE(info)) {
if (isTRUE(combine_SI)) {
cat(font_red("\nOnly results with 'R' are considered as resistance. Use `combine_SI = FALSE` to also consider 'I' as resistance.\n"))
} else {
cat(font_red("\nResults with 'R' or 'I' are considered as resistance. Use `combine_SI = TRUE` to only consider 'R' as resistance.\n"))
}
cat("\n", word_wrap("Determining multidrug-resistant organisms (MDRO), according to:"), "\n",
word_wrap(paste0(font_bold("Guideline: "), font_italic(guideline$name)), extra_indent = 11, as_note = FALSE), "\n",
word_wrap(paste0(font_bold("Author(s): "), guideline$author), extra_indent = 11, as_note = FALSE), "\n",
ifelse(!is.na(guideline$version),
paste0(word_wrap(paste0(font_bold("Version: "), guideline$version), extra_indent = 11, as_note = FALSE), "\n"),
""
),
paste0(font_bold("Source: "), guideline$source_url),
"\n\n",
sep = ""
)
}
ab_missing <- function(ab) {
isTRUE(ab %in% c(NULL, NA)) | length(ab) == 0
}
ab_NA <- function(x) {
x[!is.na(x)]
}
try_ab <- function(expr) {
out <- tryCatch(expr, error = function(e) FALSE)
out[is.na(out)] <- FALSE
out
}
# antibiotic classes
# nolint start
aminoglycosides <- c(TOB, GEN)
cephalosporins <- c(CDZ, CAC, CEC, CFR, RID, MAN, CTZ, CZD, CZO, CDR, DIT, FEP, CAT, CFM, CMX, CMZ, DIZ, CID, CFP, CSL, CND, CTX, CTT, CTF, FOX, CPM, CPO, CPD, CPR, CRD, CFS, CPT, CAZ, CCV, CTL, CTB, CZX, BPR, CFM1, CEI, CRO, CXM, LEX, CEP, HAP, CED, LTM, LOR)
cephalosporins_1st <- c(CAC, CFR, RID, CTZ, CZD, CZO, CRD, CTL, LEX, CEP, HAP, CED)
cephalosporins_2nd <- c(CEC, MAN, CMZ, CID, CND, CTT, CTF, FOX, CPR, CXM, LOR)
cephalosporins_3rd <- c(CDZ, CDR, DIT, CAT, CFM, CMX, DIZ, CFP, CSL, CTX, CPM, CPD, CFS, CAZ, CCV, CTB, CZX, CRO, LTM)
carbapenems <- c(DOR, ETP, IPM, MEM, MEV)
fluoroquinolones <- c(CIP, ENX, FLE, GAT, GEM, GRX, LVX, LOM, MFX, NOR, OFX, PAZ, PEF, PRU, RFL, SPX, TMX, TVA)
# nolint end
# helper function for editing the table
trans_tbl <- function(to, rows, cols, any_all) {
cols <- cols[!ab_missing(cols)]
cols <- cols[!is.na(cols)]
if (length(rows) > 0 && length(cols) > 0) {
x[, cols] <- as.data.frame(
lapply(
x[, cols, drop = FALSE],
function(col) as.sir(col)
),
stringsAsFactors = FALSE
)
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],
function(y) y %in% search_result
)
paste(
sort(c(
unlist(strsplit(x[row, "columns_nonsusceptible", drop = TRUE], ", ", fixed = TRUE)),
names(cols_nonsus)[cols_nonsus]
)),
collapse = ", "
)
}
)
if (any_all == "any") {
search_function <- any
} else if (any_all == "all") {
search_function <- all
}
x_transposed <- as.list(as.data.frame(t(x[, cols, drop = FALSE]),
stringsAsFactors = FALSE
))
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 (isTRUE(info)) {
message_(txt, "...", appendLF = FALSE, as_note = FALSE)
}
if (length(rows) > 0) {
# function specific for the CMI paper of 2012 (Magiorakos et al.)
lst_vector <- unlist(lst)[!is.na(unlist(lst))]
# keep only unique ones:
lst_vector <- lst_vector[!duplicated(paste(lst_vector, names(lst_vector)))]
x[, lst_vector] <- as.data.frame(
lapply(
x[, lst_vector, drop = FALSE],
function(col) as.sir(col)
),
stringsAsFactors = FALSE
)
x[rows, "classes_in_guideline"] <<- length(lst)
x[rows, "classes_available"] <<- vapply(
FUN.VALUE = double(1),
rows,
function(row, group_tbl = lst) {
sum(vapply(
FUN.VALUE = logical(1),
group_tbl,
function(group) any(unlist(x[row, group[!is.na(group)], drop = TRUE]) %in% c("S", "SDD", "I", "R"))
))
}
)
if (isTRUE(verbose)) {
x[rows, "columns_nonsusceptible"] <<- vapply(
FUN.VALUE = character(1),
rows,
function(row, group_vct = lst_vector) {
cols_nonsus <- vapply(FUN.VALUE = logical(1), x[row, group_vct, drop = FALSE], function(y) y %in% search_result)
paste(sort(names(cols_nonsus)[cols_nonsus]), collapse = ", ")
}
)
}
x[rows, "classes_affected"] <<- vapply(
FUN.VALUE = double(1),
rows,
function(row, group_tbl = lst) {
sum(
vapply(
FUN.VALUE = logical(1),
group_tbl,
function(group) {
any(unlist(x[row, group[!is.na(group)], drop = TRUE]) %in% search_result, na.rm = TRUE)
}
),
na.rm = TRUE
)
}
)
# for PDR; all drugs are R (or I if combine_SI = FALSE)
x_transposed <- as.list(as.data.frame(t(x[rows, lst_vector, drop = FALSE]),
stringsAsFactors = FALSE
))
row_filter <- vapply(FUN.VALUE = logical(1), x_transposed, function(y) all(y %in% search_result, na.rm = TRUE))
x[which(row_filter), "classes_affected"] <<- 999
}
if (isTRUE(info)) {
message_(" OK.", add_fn = list(font_green, font_bold), as_note = FALSE)
}
}
x[, col_mo] <- as.mo(as.character(x[, col_mo, drop = TRUE]))
# rename col_mo to prevent interference with joined columns
colnames(x)[colnames(x) == col_mo] <- ".col_mo"
col_mo <- ".col_mo"
# join to microorganisms data set
x <- left_join_microorganisms(x, by = col_mo)
x$MDRO <- ifelse(!is.na(x$genus), 1, NA_integer_)
x$row_number <- seq_len(nrow(x))
x$reason <- paste0("not covered by ", toupper(guideline$code), " guideline")
x$columns_nonsusceptible <- ""
if (guideline$code == "cmi2012") {
# CMI, 2012 ---------------------------------------------------------------
# Non-susceptible = R and I
# (see header 'Approaches to Creating Definitions for MDR, XDR and PDR' in paper)
# take amoxicillin if ampicillin is unavailable
if (is.na(AMP) && !is.na(AMX)) {
if (isTRUE(verbose)) {
message_("Filling ampicillin (AMP) results with amoxicillin (AMX) results")
}
AMP <- AMX
}
# take ceftriaxone if cefotaxime is unavailable and vice versa
if (is.na(CRO) && !is.na(CTX)) {
if (isTRUE(verbose)) {
message_("Filling ceftriaxone (CRO) results with cefotaxime (CTX) results")
}
CRO <- CTX
}
if (is.na(CTX) && !is.na(CRO)) {
if (isTRUE(verbose)) {
message_("Filling cefotaxime (CTX) results with ceftriaxone (CRO) results")
}
CTX <- CRO
}
# intrinsic resistant must not be considered for the determination of MDR,
# so let's just remove them, meticulously following the paper
x[which(x$genus == "Enterococcus" & x$species == "faecium"), ab_NA(IPM)] <- NA
x[which(x$genus == "Enterococcus" & x$species == "faecalis"), ab_NA(QDA)] <- NA
x[which((x$genus == "Providencia" & x$species == "rettgeri") |
(x$genus == "Providencia" & x$species == "stuartii")), ab_NA(c(GEN, TOB, NET))] <- NA
x[which(x$genus == "Escherichia" & x$species == "hermannii"), ab_NA(c(TCC, TZP))] <- NA
x[which((x$genus == "Citrobacter" & x$species == "freundii") |
(x$genus == "Enterobacter" & x$species == "aerogenes") |
(x$genus == "Klebsiella" & x$species == "aerogenes") # new name (2017)
| (x$genus == "Enterobacter" & x$species == "cloacae") |
(x$genus == "Hafnia" & x$species == "alvei") |
(x$genus == "Morganella" & x$species == "morganii") |
(x$genus == "Proteus" & x$species == "penneri") |
(x$genus == "Proteus" & x$species == "vulgaris") |
(x$genus == "Serratia" & x$species == "marcescens")), ab_NA(CZO)] <- NA
x[which((x$genus == "Morganella" & x$species == "morganii") |
(x$genus == "Proteus" & x$species == "penneri") |
(x$genus == "Proteus" & x$species == "vulgaris") |
(x$genus == "Serratia" & x$species == "marcescens")), ab_NA(CXM)] <- NA
x[which((x$genus == "Morganella" & x$species == "morganii") |
(x$genus == "Proteus" & x$species == "mirabilis") |
(x$genus == "Proteus" & x$species == "penneri") |
(x$genus == "Proteus" & x$species == "vulgaris") |
(x$genus == "Providencia" & x$species == "rettgeri") |
(x$genus == "Providencia" & x$species == "stuartii")), ab_NA(TGC)] <- NA
x[which((x$genus == "Citrobacter" & x$species == "koseri") |
(x$genus == "Citrobacter" & x$species == "freundii") |
(x$genus == "Enterobacter" & x$species == "aerogenes") |
(x$genus == "Klebsiella" & x$species == "aerogenes") # new name (2017)
| (x$genus == "Enterobacter" & x$species == "cloacae") |
(x$genus == "Escherichia" & x$species == "hermannii") |
(x$genus == "Hafnia" & x$species == "alvei") |
(x$genus == "Klebsiella") |
(x$genus == "Morganella" & x$species == "morganii") |
(x$genus == "Proteus" & x$species == "penneri") |
(x$genus == "Proteus" & x$species == "vulgaris") |
(x$genus == "Providencia" & x$species == "rettgeri") |
(x$genus == "Providencia" & x$species == "stuartii") |
(x$genus == "Serratia" & x$species == "marcescens")), ab_NA(AMP)] <- NA
x[which((x$genus == "Citrobacter" & x$species == "freundii") |
(x$genus == "Enterobacter" & x$species == "aerogenes") |
(x$genus == "Klebsiella" & x$species == "aerogenes") # new name (2017)
| (x$genus == "Enterobacter" & x$species == "cloacae") |
(x$genus == "Hafnia" & x$species == "alvei") |
(x$genus == "Morganella" & x$species == "morganii") |
(x$genus == "Providencia" & x$species == "rettgeri") |
(x$genus == "Providencia" & x$species == "stuartii") |
(x$genus == "Serratia" & x$species == "marcescens")), ab_NA(AMC)] <- NA
x[which((x$genus == "Citrobacter" & x$species == "freundii") |
(x$genus == "Citrobacter" & x$species == "koseri") |
(x$genus == "Enterobacter" & x$species == "aerogenes") |
(x$genus == "Klebsiella" & x$species == "aerogenes") # new name (2017)
| (x$genus == "Enterobacter" & x$species == "cloacae") |
(x$genus == "Hafnia" & x$species == "alvei") |
(x$genus == "Providencia" & x$species == "rettgeri") |
(x$genus == "Serratia" & x$species == "marcescens")), ab_NA(SAM)] <- NA
x[which((x$genus == "Morganella" & x$species == "morganii") |
(x$genus == "Proteus" & x$species == "mirabilis") |
(x$genus == "Proteus" & x$species == "penneri") |
(x$genus == "Proteus" & x$species == "vulgaris") |
(x$genus == "Providencia" & x$species == "rettgeri") |
(x$genus == "Providencia" & x$species == "stuartii") |
(x$genus == "Serratia" & x$species == "marcescens")), ab_NA(COL)] <- NA
x[which((x$genus == "Morganella" & x$species == "morganii") |
(x$genus == "Proteus" & x$species == "mirabilis") |
(x$genus == "Proteus" & x$species == "penneri") |
(x$genus == "Proteus" & x$species == "vulgaris") |
(x$genus == "Providencia" & x$species == "rettgeri") |
(x$genus == "Providencia" & x$species == "stuartii")), ab_NA(TCY)] <- NA
x[which((x$genus == "Morganella" & x$species == "morganii") |
(x$genus == "Proteus" & x$species == "penneri") |
(x$genus == "Proteus" & x$species == "vulgaris") |
(x$genus == "Providencia" & x$species == "rettgeri") |
(x$genus == "Providencia" & x$species == "stuartii")), ab_NA(c(DOX, MNO))] <- NA
x$classes_in_guideline <- NA_integer_
x$classes_available <- NA_integer_
x$classes_affected <- NA_integer_
# now add the MDR levels to the data
trans_tbl(
2,
which(x$genus == "Staphylococcus" & x$species == "aureus"),
c(OXA, FOX),
"any"
)
trans_tbl2(
paste("Table 1 -", font_italic("Staphylococcus aureus")),
which(x$genus == "Staphylococcus" & x$species == "aureus"),
list(
GEN,
RIF,
CPT,
c(OXA, FOX),
c(CIP, MFX),
SXT,
FUS,
c(VAN, TEC, TLV),
TGC,
CLI,
DAP,
ERY,
LNZ,
CHL,
FOS,
QDA,
c(TCY, DOX, MNO)
)
)
trans_tbl2(
paste("Table 2 -", font_italic("Enterococcus"), "spp."),
which(x$genus == "Enterococcus"),
list(
GEH,
STH,
c(IPM, MEM, DOR),
c(CIP, LVX, MFX),
c(VAN, TEC),
TGC,
DAP,
LNZ,
AMP,
QDA,
c(DOX, MNO)
)
)
trans_tbl2(
paste0("Table 3 - ", font_italic("Enterobacteriaceae")),
# this new order was previously 'Enterobacteriales' and contained only the family 'Enterobacteriaceae':
which(x$order == "Enterobacterales"),
list(
c(GEN, TOB, AMK, NET),
CPT,
c(TCC, TZP),
c(ETP, IPM, MEM, DOR),
CZO,
CXM,
c(CTX, CAZ, FEP),
c(FOX, CTT),
CIP,
SXT,
TGC,
ATM,
AMP,
c(AMC, SAM),
CHL,
FOS,
COL,
c(TCY, DOX, MNO)
)
)
trans_tbl2(
paste("Table 4 -", font_italic("Pseudomonas aeruginosa")),
which(x$genus == "Pseudomonas" & x$species == "aeruginosa"),
list(
c(GEN, TOB, AMK, NET),
c(IPM, MEM, DOR),
c(CAZ, FEP),
c(CIP, LVX),
c(TCC, TZP),
ATM,
FOS,
c(COL, PLB)
)
)
trans_tbl2(
paste("Table 5 -", font_italic("Acinetobacter"), "spp."),
which(x$genus == "Acinetobacter"),
list(
c(GEN, TOB, AMK, NET),
c(IPM, MEM, DOR),
c(CIP, LVX),
c(TZP, TCC),
c(CTX, CRO, CAZ, FEP),
SXT,
SAM,
c(COL, PLB),
c(TCY, DOX, MNO)
)
)
# now set MDROs:
# MDR (=2): >=3 classes affected
x[which(x$classes_affected >= 3), "MDRO"] <- 2