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570 lines
22 KiB
R
Executable File
570 lines
22 KiB
R
Executable File
# ==================================================================== #
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# TITLE #
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# Antimicrobial Resistance (AMR) Analysis for R #
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# #
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# SOURCE #
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# https://github.com/msberends/AMR #
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# #
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# LICENCE #
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# (c) 2018-2020 Berends MS, Luz CF et al. #
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# Developed at the University of Groningen, the Netherlands, in #
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# collaboration with non-profit organisations Certe Medical #
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# Diagnostics & Advice, and University Medical Center Groningen. #
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# #
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# This R package is free software; you can freely use and distribute #
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# it for both personal and commercial purposes under the terms of the #
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# GNU General Public License version 2.0 (GNU GPL-2), as published by #
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# the Free Software Foundation. #
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# We created this package for both routine data analysis and academic #
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# research and it was publicly released in the hope that it will be #
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# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
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# #
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# Visit our website for the full manual and a complete tutorial about #
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# how to conduct AMR analysis: https://msberends.github.io/AMR/ #
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# ==================================================================== #
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#' Transform input to an antibiotic ID
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#'
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#' Use this function to determine the antibiotic code of one or more antibiotics. The data set [antibiotics] will be searched for abbreviations, official names and synonyms (brand names).
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#' @inheritSection lifecycle Stable lifecycle
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#' @param x character vector to determine to antibiotic ID
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#' @param flag_multiple_results logical to indicate whether a note should be printed to the console that probably more than one antibiotic code or name can be retrieved from a single input value.
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#' @param info logical to indicate whether a progress bar should be printed
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#' @param ... arguments passed on to internal functions
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#' @rdname as.ab
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#' @inheritSection WHOCC WHOCC
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#' @details All entries in the [antibiotics] data set have three different identifiers: a human readable EARS-Net code (column `ab`, used by ECDC and WHONET), an ATC code (column `atc`, used by WHO), and a CID code (column `cid`, Compound ID, used by PubChem). The data set contains more than 5,000 official brand names from many different countries, as found in PubChem.
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#'
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#' All these properties will be searched for the user input. The [as.ab()] can correct for different forms of misspelling:
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#'
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#' * Wrong spelling of drug names (like "tobramicin" or "gentamycin"), which corrects for most audible similarities such as f/ph, x/ks, c/z/s, t/th, etc.
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#' * Too few or too many vowels or consonants
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#' * Switching two characters (like "mreopenem", often the case in clinical data, when doctors typed too fast)
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#' * Digitalised paper records, leaving artefacts like 0/o/O (zero and O's), B/8, n/r, etc.
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#'
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#' Use the [ab_property()] functions to get properties based on the returned antibiotic ID, see Examples.
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#'
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#' @section Source:
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#' World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology: \url{https://www.whocc.no/atc_ddd_index/}
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#'
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#' WHONET 2019 software: \url{http://www.whonet.org/software.html}
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#'
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#' European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: \url{http://ec.europa.eu/health/documents/community-register/html/atc.htm}
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#' @aliases ab
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#' @return A [character] [vector] with additional class [`ab`]
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#' @seealso
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#' * [antibiotics] for the [data.frame] that is being used to determine ATCs
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#' * [ab_from_text()] for a function to retrieve antimicrobial drugs from clinical text (from health care records)
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#' @inheritSection AMR Reference data publicly available
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#' @inheritSection AMR Read more on our website!
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#' @export
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#' @examples
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#' # these examples all return "ERY", the ID of erythromycin:
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#' as.ab("J01FA01")
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#' as.ab("J 01 FA 01")
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#' as.ab("Erythromycin")
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#' as.ab("eryt")
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#' as.ab(" eryt 123")
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#' as.ab("ERYT")
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#' as.ab("ERY")
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#' as.ab("eritromicine") # spelled wrong, yet works
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#' as.ab("Erythrocin") # trade name
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#' as.ab("Romycin") # trade name
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#'
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#' # spelling from different languages and dyslexia are no problem
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#' ab_atc("ceftriaxon")
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#' ab_atc("cephtriaxone") # small spelling error
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#' ab_atc("cephthriaxone") # or a bit more severe
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#' ab_atc("seephthriaaksone") # and even this works
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#'
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#' # use ab_* functions to get a specific properties (see ?ab_property);
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#' # they use as.ab() internally:
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#' ab_name("J01FA01") # "Erythromycin"
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#' ab_name("eryt") # "Erythromycin"
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as.ab <- function(x, flag_multiple_results = TRUE, info = TRUE, ...) {
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meet_criteria(x, allow_class = c("character", "numeric", "integer", "factor"), allow_NA = TRUE)
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meet_criteria(flag_multiple_results, allow_class = "logical", has_length = 1)
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meet_criteria(info, allow_class = "logical", has_length = 1)
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check_dataset_integrity()
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if (is.ab(x)) {
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return(x)
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}
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initial_search <- is.null(list(...)$initial_search)
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already_regex <- isTRUE(list(...)$already_regex)
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if (all(toupper(x) %in% antibiotics$ab)) {
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# valid AB code, but not yet right class
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return(structure(.Data = toupper(x),
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class = c("ab", "character")))
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}
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x_bak <- x
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x <- toupper(x)
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# remove diacritics
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x <- iconv(x, from = "UTF-8", to = "ASCII//TRANSLIT")
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x <- gsub('"', "", x, fixed = TRUE)
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x <- gsub("(specimen|specimen date|specimen_date|spec_date)", "", x, ignore.case = TRUE, perl = TRUE)
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x_bak_clean <- x
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if (already_regex == FALSE) {
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x_bak_clean <- generalise_antibiotic_name(x_bak_clean)
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}
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x <- unique(x_bak_clean) # this means that every x is in fact generalise_antibiotic_name(x)
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x_new <- rep(NA_character_, length(x))
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x_unknown <- character(0)
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note_if_more_than_one_found <- function(found, index, from_text) {
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if (initial_search == TRUE & isTRUE(length(from_text) > 1)) {
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abnames <- ab_name(from_text, tolower = TRUE, initial_search = FALSE)
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if (ab_name(found[1L], language = NULL) %like% "clavulanic acid") {
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abnames <- abnames[!abnames == "clavulanic acid"]
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}
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if (length(abnames) > 1) {
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message(font_blue(paste0("NOTE: more than one result was found for item ", index, ": ",
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paste0(abnames, collapse = ", "))))
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}
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}
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found[1L]
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}
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if (initial_search == TRUE) {
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progress <- progress_ticker(n = length(x), n_min = ifelse(isTRUE(info), 25, length(x) + 1)) # start if n >= 25
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on.exit(close(progress))
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}
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for (i in seq_len(length(x))) {
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if (initial_search == TRUE) {
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progress$tick()
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}
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if (is.na(x[i]) | is.null(x[i])) {
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next
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}
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if (identical(x[i], "") |
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# no short names:
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nchar(x[i]) <= 2 |
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# prevent "bacteria" from coercing to TMP, since Bacterial is a brand name of it:
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identical(tolower(x[i]), "bacteria")) {
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x_unknown <- c(x_unknown, x_bak[x[i] == x_bak_clean][1])
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next
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}
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if (isTRUE(flag_multiple_results) & x[i] %like% "[ ]") {
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from_text <- suppressWarnings(ab_from_text(x[i], initial_search = FALSE, translate_ab = FALSE)[[1]])
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} else {
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from_text <- character(0)
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}
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# exact name
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found <- antibiotics[which(AB_lookup$generalised_name == x[i]), ]$ab
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if (length(found) > 0) {
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x_new[i] <- found[1L]
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next
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}
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# exact AB code
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found <- antibiotics[which(antibiotics$ab == x[i]), ]$ab
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if (length(found) > 0) {
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x_new[i] <- note_if_more_than_one_found(found, i, from_text)
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next
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}
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# exact ATC code
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found <- antibiotics[which(antibiotics$atc == x[i]), ]$ab
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if (length(found) > 0) {
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x_new[i] <- note_if_more_than_one_found(found, i, from_text)
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next
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}
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# exact CID code
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found <- antibiotics[which(antibiotics$cid == x[i]), ]$ab
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if (length(found) > 0) {
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x_new[i] <- note_if_more_than_one_found(found, i, from_text)
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next
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}
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# exact LOINC code
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loinc_found <- unlist(lapply(AB_lookup$generalised_loinc,
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function(s) x[i] %in% s))
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found <- antibiotics$ab[loinc_found == TRUE]
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if (length(found) > 0) {
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x_new[i] <- note_if_more_than_one_found(found, i, from_text)
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next
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}
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# exact synonym
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synonym_found <- unlist(lapply(AB_lookup$generalised_synonyms,
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function(s) x[i] %in% s))
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found <- antibiotics$ab[synonym_found == TRUE]
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if (length(found) > 0) {
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x_new[i] <- note_if_more_than_one_found(found, i, from_text)
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next
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}
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# exact abbreviation
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abbr_found <- unlist(lapply(AB_lookup$generalised_abbreviations,
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function(s) x[i] %in% s))
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found <- antibiotics$ab[abbr_found == TRUE]
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if (length(found) > 0) {
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x_new[i] <- note_if_more_than_one_found(found, i, from_text)
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next
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}
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# allow characters that resemble others, but only continue when having more than 3 characters
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if (nchar(x[i]) <= 3) {
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x_unknown <- c(x_unknown, x_bak[x[i] == x_bak_clean][1])
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next
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}
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x_spelling <- x[i]
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if (already_regex == FALSE) {
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x_spelling <- gsub("[IY]+", "[IY]+", x_spelling, perl = TRUE)
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x_spelling <- gsub("(C|K|Q|QU|S|Z|X|KS)+", "(C|K|Q|QU|S|Z|X|KS)+", x_spelling, perl = TRUE)
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x_spelling <- gsub("(PH|F|V)+", "(PH|F|V)+", x_spelling, perl = TRUE)
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x_spelling <- gsub("(TH|T)+", "(TH|T)+", x_spelling, perl = TRUE)
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x_spelling <- gsub("A+", "A+", x_spelling, perl = TRUE)
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x_spelling <- gsub("E+", "E+", x_spelling, perl = TRUE)
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x_spelling <- gsub("O+", "O+", x_spelling, perl = TRUE)
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# allow any ending of -in/-ine and -im/-ime
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x_spelling <- gsub("(\\[IY\\]\\+(N|M)|\\[IY\\]\\+(N|M)E\\+)$", "[IY]+(N|M)E*", x_spelling, perl = TRUE)
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# allow any ending of -ol/-ole
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x_spelling <- gsub("(O\\+L|O\\+LE\\+)$", "O+LE*", x_spelling, perl = TRUE)
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# allow any ending of -on/-one
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x_spelling <- gsub("(O\\+N|O\\+NE\\+)$", "O+NE*", x_spelling, perl = TRUE)
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# replace multiple same characters to single one with '+', like "ll" -> "l+"
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x_spelling <- gsub("(.)\\1+", "\\1+", x_spelling, perl = TRUE)
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# replace spaces and slashes with a possibility on both
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x_spelling <- gsub("[ /]", "( .*|.*/)", x_spelling, perl = TRUE)
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# correct for digital reading text (OCR)
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x_spelling <- gsub("[NRD8B]", "[NRD8B]", x_spelling, perl = TRUE)
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x_spelling <- gsub("(O|0)", "(O|0)+", x_spelling, perl = TRUE)
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x_spelling <- gsub("++", "+", x_spelling, fixed = TRUE)
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}
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# try if name starts with it
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found <- antibiotics[which(AB_lookup$generalised_name %like% paste0("^", x_spelling)), ]$ab
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if (length(found) > 0) {
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x_new[i] <- note_if_more_than_one_found(found, i, from_text)
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next
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}
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# try if name ends with it
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found <- antibiotics[which(AB_lookup$generalised_name %like% paste0(x_spelling, "$")), ]$ab
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if (nchar(x[i]) >= 4 & length(found) > 0) {
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x_new[i] <- note_if_more_than_one_found(found, i, from_text)
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next
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}
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# and try if any synonym starts with it
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synonym_found <- unlist(lapply(AB_lookup$generalised_synonyms,
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function(s) any(s %like% paste0("^", x_spelling))))
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found <- antibiotics$ab[synonym_found == TRUE]
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if (length(found) > 0) {
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x_new[i] <- note_if_more_than_one_found(found, i, from_text)
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next
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}
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# INITIAL SEARCH - More uncertain results ----
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if (initial_search == TRUE) {
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# only run on first try
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# try by removing all spaces
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if (x[i] %like% " ") {
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found <- suppressWarnings(as.ab(gsub(" +", "", x[i], perl = TRUE), initial_search = FALSE))
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if (length(found) > 0 & !is.na(found)) {
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x_new[i] <- note_if_more_than_one_found(found, i, from_text)
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next
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}
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}
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# try by removing all spaces and numbers
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if (x[i] %like% " " | x[i] %like% "[0-9]") {
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found <- suppressWarnings(as.ab(gsub("[ 0-9]", "", x[i], perl = TRUE), initial_search = FALSE))
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if (length(found) > 0 & !is.na(found)) {
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x_new[i] <- note_if_more_than_one_found(found, i, from_text)
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next
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}
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}
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# transform back from other languages and try again
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x_translated <- paste(lapply(strsplit(x[i], "[^A-Z0-9]"),
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function(y) {
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for (i in seq_len(length(y))) {
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y[i] <- ifelse(tolower(y[i]) %in% tolower(translations_file$replacement),
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translations_file[which(tolower(translations_file$replacement) == tolower(y[i]) &
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!isFALSE(translations_file$fixed)), "pattern"],
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y[i])
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}
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generalise_antibiotic_name(y)
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})[[1]],
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collapse = "/")
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x_translated_guess <- suppressWarnings(as.ab(x_translated, initial_search = FALSE))
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if (!is.na(x_translated_guess)) {
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x_new[i] <- x_translated_guess
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next
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}
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# now also try to coerce brandname combinations like "Amoxy/clavulanic acid"
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x_translated <- paste(lapply(strsplit(x_translated, "[^A-Z0-9 ]"),
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function(y) {
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for (i in seq_len(length(y))) {
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y_name <- suppressWarnings(ab_name(y[i], language = NULL, initial_search = FALSE))
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y[i] <- ifelse(!is.na(y_name),
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y_name,
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y[i])
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}
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generalise_antibiotic_name(y)
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})[[1]],
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collapse = "/")
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x_translated_guess <- suppressWarnings(as.ab(x_translated, initial_search = FALSE))
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if (!is.na(x_translated_guess)) {
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x_new[i] <- x_translated_guess
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next
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}
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# try by removing all trailing capitals
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if (x[i] %like_case% "[a-z]+[A-Z]+$") {
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found <- suppressWarnings(as.ab(gsub("[A-Z]+$", "", x[i], perl = TRUE), initial_search = FALSE))
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if (!is.na(found)) {
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x_new[i] <- note_if_more_than_one_found(found, i, from_text)
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next
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}
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}
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# keep only letters
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found <- suppressWarnings(as.ab(gsub("[^A-Z]", "", x[i], perl = TRUE), initial_search = FALSE))
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if (!is.na(found)) {
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x_new[i] <- note_if_more_than_one_found(found, i, from_text)
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next
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}
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# try from a bigger text, like from a health care record, see ?ab_from_text
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# already calculated above if flag_multiple_results = TRUE
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if (isTRUE(flag_multiple_results)) {
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found <- from_text[1L]
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} else {
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found <- suppressWarnings(ab_from_text(x[i], initial_search = FALSE, translate_ab = FALSE)[[1]][1L])
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}
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if (!is.na(found)) {
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x_new[i] <- note_if_more_than_one_found(found, i, from_text)
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next
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}
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# first 5 except for cephalosporins, then first 7 (those cephalosporins all start quite the same!)
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found <- suppressWarnings(as.ab(substr(x[i], 1, 5), initial_search = FALSE))
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if (!is.na(found) && !ab_group(found, initial_search = FALSE) %like% "cephalosporins") {
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x_new[i] <- note_if_more_than_one_found(found, i, from_text)
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next
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}
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found <- suppressWarnings(as.ab(substr(x[i], 1, 7), initial_search = FALSE))
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if (!is.na(found)) {
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x_new[i] <- note_if_more_than_one_found(found, i, from_text)
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next
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}
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# make all consonants facultative
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search_str <- gsub("([BCDFGHJKLMNPQRSTVWXZ])", "\\1*", x[i], perl = TRUE)
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found <- suppressWarnings(as.ab(search_str, initial_search = FALSE, already_regex = TRUE))
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# keep at least 4 normal characters
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if (nchar(gsub(".\\*", "", search_str, perl = TRUE)) < 4) {
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found <- NA
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}
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if (!is.na(found)) {
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x_new[i] <- note_if_more_than_one_found(found, i, from_text)
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next
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}
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# make all vowels facultative
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search_str <- gsub("([AEIOUY])", "\\1*", x[i], perl = TRUE)
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found <- suppressWarnings(as.ab(search_str, initial_search = FALSE, already_regex = TRUE))
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# keep at least 5 normal characters
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if (nchar(gsub(".\\*", "", search_str, perl = TRUE)) < 5) {
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found <- NA
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}
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if (!is.na(found)) {
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x_new[i] <- note_if_more_than_one_found(found, i, from_text)
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next
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}
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# allow misspelling of vowels
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x_spelling <- gsub("A+", "[AEIOU]+", x_spelling, fixed = TRUE)
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x_spelling <- gsub("E+", "[AEIOU]+", x_spelling, fixed = TRUE)
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x_spelling <- gsub("I+", "[AEIOU]+", x_spelling, fixed = TRUE)
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x_spelling <- gsub("O+", "[AEIOU]+", x_spelling, fixed = TRUE)
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x_spelling <- gsub("U+", "[AEIOU]+", x_spelling, fixed = TRUE)
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found <- suppressWarnings(as.ab(x_spelling, initial_search = FALSE, already_regex = TRUE))
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if (!is.na(found)) {
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x_new[i] <- note_if_more_than_one_found(found, i, from_text)
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next
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}
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# try with switched character, like "mreopenem"
|
|
for (j in seq_len(nchar(x[i]))) {
|
|
x_switched <- paste0(
|
|
# beginning part:
|
|
substr(x[i], 1, j - 1),
|
|
# here is the switching of 2 characters:
|
|
substr(x[i], j + 1, j + 1),
|
|
substr(x[i], j, j),
|
|
# ending part:
|
|
substr(x[i], j + 2, nchar(x[i])))
|
|
found <- suppressWarnings(as.ab(x_switched, initial_search = FALSE))
|
|
if (!is.na(found)) {
|
|
break
|
|
}
|
|
}
|
|
if (!is.na(found)) {
|
|
x_new[i] <- found[1L]
|
|
next
|
|
}
|
|
|
|
} # end of initial_search = TRUE
|
|
|
|
# not found
|
|
x_unknown <- c(x_unknown, x_bak[x[i] == x_bak_clean][1])
|
|
}
|
|
|
|
if (initial_search == TRUE) {
|
|
close(progress)
|
|
}
|
|
|
|
# take failed ATC codes apart from rest
|
|
x_unknown_ATCs <- x_unknown[x_unknown %like% "[A-Z][0-9][0-9][A-Z][A-Z][0-9][0-9]"]
|
|
x_unknown <- x_unknown[!x_unknown %in% x_unknown_ATCs]
|
|
if (length(x_unknown_ATCs) > 0) {
|
|
warning("These ATC codes are not (yet) in the antibiotics data set: ",
|
|
paste('"', sort(unique(x_unknown_ATCs)), '"', sep = "", collapse = ", "),
|
|
".",
|
|
call. = FALSE)
|
|
}
|
|
|
|
if (length(x_unknown) > 0) {
|
|
warning("These values could not be coerced to a valid antimicrobial ID: ",
|
|
paste('"', sort(unique(x_unknown)), '"', sep = "", collapse = ", "),
|
|
".",
|
|
call. = FALSE)
|
|
}
|
|
|
|
x_result <- data.frame(x = x_bak_clean, stringsAsFactors = FALSE) %pm>%
|
|
pm_left_join(data.frame(x = x, x_new = x_new, stringsAsFactors = FALSE), by = "x") %pm>%
|
|
pm_pull(x_new)
|
|
|
|
if (length(x_result) == 0) {
|
|
x_result <- NA_character_
|
|
}
|
|
|
|
structure(.Data = x_result,
|
|
class = c("ab", "character"))
|
|
}
|
|
|
|
#' @rdname as.ab
|
|
#' @export
|
|
is.ab <- function(x) {
|
|
inherits(x, "ab")
|
|
}
|
|
|
|
# will be exported using s3_register() in R/zzz.R
|
|
pillar_shaft.ab <- function(x, ...) {
|
|
out <- trimws(format(x))
|
|
out[is.na(x)] <- font_na(NA)
|
|
create_pillar_column(out, align = "left", min_width = 4)
|
|
}
|
|
|
|
# will be exported using s3_register() in R/zzz.R
|
|
type_sum.ab <- function(x, ...) {
|
|
"ab"
|
|
}
|
|
|
|
#' @method print ab
|
|
#' @export
|
|
#' @noRd
|
|
print.ab <- function(x, ...) {
|
|
cat("Class <ab>\n")
|
|
print(as.character(x), quote = FALSE)
|
|
}
|
|
|
|
#' @method as.data.frame ab
|
|
#' @export
|
|
#' @noRd
|
|
as.data.frame.ab <- function(x, ...) {
|
|
nm <- deparse1(substitute(x))
|
|
if (!"nm" %in% names(list(...))) {
|
|
as.data.frame.vector(as.ab(x), ..., nm = nm)
|
|
} else {
|
|
as.data.frame.vector(as.ab(x), ...)
|
|
}
|
|
}
|
|
#' @method [ ab
|
|
#' @export
|
|
#' @noRd
|
|
"[.ab" <- function(x, ...) {
|
|
y <- NextMethod()
|
|
attributes(y) <- attributes(x)
|
|
y
|
|
}
|
|
#' @method [[ ab
|
|
#' @export
|
|
#' @noRd
|
|
"[[.ab" <- function(x, ...) {
|
|
y <- NextMethod()
|
|
attributes(y) <- attributes(x)
|
|
y
|
|
}
|
|
#' @method [<- ab
|
|
#' @export
|
|
#' @noRd
|
|
"[<-.ab" <- function(i, j, ..., value) {
|
|
y <- NextMethod()
|
|
attributes(y) <- attributes(i)
|
|
class_integrity_check(y, "antimicrobial code", antibiotics$ab)
|
|
}
|
|
#' @method [[<- ab
|
|
#' @export
|
|
#' @noRd
|
|
"[[<-.ab" <- function(i, j, ..., value) {
|
|
y <- NextMethod()
|
|
attributes(y) <- attributes(i)
|
|
class_integrity_check(y, "antimicrobial code", antibiotics$ab)
|
|
}
|
|
#' @method c ab
|
|
#' @export
|
|
#' @noRd
|
|
c.ab <- function(x, ...) {
|
|
y <- NextMethod()
|
|
attributes(y) <- attributes(x)
|
|
class_integrity_check(y, "antimicrobial code", antibiotics$ab)
|
|
}
|
|
|
|
#' @method unique ab
|
|
#' @export
|
|
#' @noRd
|
|
unique.ab <- function(x, incomparables = FALSE, ...) {
|
|
y <- NextMethod()
|
|
attributes(y) <- attributes(x)
|
|
y
|
|
}
|
|
|
|
generalise_antibiotic_name <- function(x) {
|
|
x <- toupper(x)
|
|
# remove suffices
|
|
x <- gsub("_(MIC|RSI|DIS[CK])$", "", x, perl = TRUE)
|
|
# remove disk concentrations, like LVX_NM -> LVX
|
|
x <- gsub("_[A-Z]{2}[0-9_.]{0,3}$", "", x, perl = TRUE)
|
|
# remove part between brackets if that's followed by another string
|
|
x <- gsub("(.*)+ [(].*[)]", "\\1", x)
|
|
# keep only max 1 space
|
|
x <- trimws2(gsub(" +", " ", x, perl = TRUE))
|
|
# non-character, space or number should be a slash
|
|
x <- gsub("[^A-Z0-9 -]", "/", x, perl = TRUE)
|
|
# spaces around non-characters must be removed: amox + clav -> amox/clav
|
|
x <- gsub("(.*[A-Z0-9]) ([^A-Z0-9].*)", "\\1\\2", x, perl = TRUE)
|
|
x <- gsub("(.*[^A-Z0-9]) ([A-Z0-9].*)", "\\1\\2", x, perl = TRUE)
|
|
# remove hyphen after a starting "co"
|
|
x <- gsub("^CO-", "CO", x, perl = TRUE)
|
|
# replace operators with a space
|
|
x <- gsub("(/| AND | WITH | W/|[+]|[-])+", " ", x, perl = TRUE)
|
|
x
|
|
}
|