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412 lines
15 KiB
R
Executable File
412 lines
15 KiB
R
Executable File
# ==================================================================== #
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# TITLE #
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# Antimicrobial Resistance (AMR) Analysis #
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# #
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# SOURCE #
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# https://gitlab.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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# #
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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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# #
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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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# Visit our website for more info: https://msberends.gitlab.io/AMR. #
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# ==================================================================== #
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#' Transform to 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 Maturing lifecycle
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#' @param x character vector to determine to antibiotic ID
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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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#' @importFrom dplyr %>% filter slice pull
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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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#' Use the [ab_property()] functions to get properties based on the returned antibiotic ID, see Examples.
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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 Character (vector) with class [`ab`]. Unknown values will return `NA`.
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#' @seealso [antibiotics] for the dataframe that is being used to determine ATCs.
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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, ...) {
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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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if (all(toupper(x) %in% antibiotics$ab)) {
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# valid AB code, but not yet right class
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return(structure(.Data = toupper(x),
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class = "ab"))
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}
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x_bak <- x
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# remove diacritics
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x <- iconv(x, from = "UTF-8", to = "ASCII//TRANSLIT")
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x <- gsub('"', "", x, fixed = TRUE)
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# remove suffices
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x_bak_clean <- gsub("_(mic|rsi|dis[ck])$", "", x, ignore.case = TRUE)
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# remove disk concentrations, like LVX_NM -> LVX
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x_bak_clean <- gsub("_[A-Z]{2}[0-9_.]{0,3}$", "", x_bak_clean, ignore.case = TRUE)
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# remove part between brackets if that's followed by another string
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x_bak_clean <- gsub("(.*)+ [(].*[)]", "\\1", x_bak_clean)
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# keep only max 1 space
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x_bak_clean <- trimws(gsub(" +", " ", x_bak_clean, ignore.case = TRUE))
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# non-character, space or number should be a slash
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x_bak_clean <- gsub("[^A-Za-z0-9 -]", "/", x_bak_clean)
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# spaces around non-characters must be removed: amox + clav -> amox/clav
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x_bak_clean <- gsub("(.*[a-zA-Z0-9]) ([^a-zA-Z0-9].*)", "\\1\\2", x_bak_clean)
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x_bak_clean <- gsub("(.*[^a-zA-Z0-9]) ([a-zA-Z0-9].*)", "\\1\\2", x_bak_clean)
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# remove hyphen after a starting "co"
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x_bak_clean <- gsub("^co-", "co", x_bak_clean, ignore.case = TRUE)
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# replace text 'and' with a slash
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x_bak_clean <- gsub(" and ", "/", x_bak_clean, ignore.case = TRUE)
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x <- unique(x_bak_clean)
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x_new <- rep(NA_character_, length(x))
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x_unknown <- character(0)
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for (i in seq_len(length(x))) {
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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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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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# prevent "bacteria" from coercing to TMP, since Bacterial is a brand name of it
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if (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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# exact AB code
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found <- antibiotics[which(antibiotics$ab == toupper(x[i])), ]$ab
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if (length(found) > 0) {
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x_new[i] <- found[1L]
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next
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}
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# exact ATC code
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found <- antibiotics[which(antibiotics$atc == toupper(x[i])), ]$ab
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if (length(found) > 0) {
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x_new[i] <- found[1L]
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next
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}
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# exact CID code
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found <- antibiotics[which(antibiotics$cid == x[i]), ]$ab
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if (length(found) > 0) {
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x_new[i] <- found[1L]
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next
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}
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# exact name
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found <- antibiotics[which(toupper(antibiotics$name) == toupper(x[i])), ]$ab
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if (length(found) > 0) {
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x_new[i] <- found[1L]
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next
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}
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# exact LOINC code
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loinc_found <- unlist(lapply(antibiotics$loinc,
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function(s) if (x[i] %in% s) {
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TRUE
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} else {
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FALSE
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}))
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found <- antibiotics$ab[loinc_found == TRUE]
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if (length(found) > 0) {
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x_new[i] <- found[1L]
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next
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}
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# exact synonym
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synonym_found <- unlist(lapply(antibiotics$synonyms,
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function(s) if (toupper(x[i]) %in% toupper(s)) {
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TRUE
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} else {
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FALSE
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}))
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found <- antibiotics$ab[synonym_found == TRUE]
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if (length(found) > 0) {
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x_new[i] <- found[1L]
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next
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}
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# exact abbreviation
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abbr_found <- unlist(lapply(antibiotics$abbreviations,
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function(a) if (toupper(x[i]) %in% toupper(a)) {
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TRUE
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} else {
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FALSE
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}))
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found <- antibiotics$ab[abbr_found == TRUE]
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if (length(found) > 0) {
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x_new[i] <- found[1L]
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next
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}
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# first >=4 characters of name
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if (nchar(x[i]) >= 4) {
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found <- antibiotics[which(toupper(antibiotics$name) %like% paste0("^", x[i])), ]$ab
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if (length(found) > 0) {
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x_new[i] <- found[1L]
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next
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}
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}
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# allow characters that resemble others, but only continue when having more than 3 characters
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if (nchar(x[i]) <= 3) {
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x_unknown <- c(x_unknown, x_bak[x[i] == x_bak_clean][1])
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next
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}
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x_spelling <- tolower(x[i])
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x_spelling <- gsub("[iy]+", "[iy]+", x_spelling)
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x_spelling <- gsub("(c|k|q|qu|s|z|x|ks)+", "(c|k|q|qu|s|z|x|ks)+", x_spelling)
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x_spelling <- gsub("(ph|f|v)+", "(ph|f|v)+", x_spelling)
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x_spelling <- gsub("(th|t)+", "(th|t)+", x_spelling)
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x_spelling <- gsub("a+", "a+", x_spelling)
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x_spelling <- gsub("e+", "e+", x_spelling)
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x_spelling <- gsub("o+", "o+", x_spelling)
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# allow any ending of -in/-ine and -im/-ime
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x_spelling <- gsub("(\\[iy\\]\\+(n|m)|\\[iy\\]\\+(n|m)e\\+)$", "[iy]+(n|m)e*", x_spelling)
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# allow any ending of -ol/-ole
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x_spelling <- gsub("(o\\+l|o\\+le\\+)$", "o+le*", x_spelling)
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# allow any ending of -on/-one
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x_spelling <- gsub("(o\\+n|o\\+ne\\+)$", "o+ne*", x_spelling)
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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)
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# try if name starts with it
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found <- antibiotics[which(antibiotics$name %like% paste0("^", x_spelling)), ]$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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# and try if any synonym starts with it
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synonym_found <- unlist(lapply(antibiotics$synonyms,
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function(s) if (any(s %like% paste0("^", x_spelling))) {
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TRUE
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} else {
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FALSE
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}))
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found <- antibiotics$ab[synonym_found == TRUE]
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if (length(found) > 0) {
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x_new[i] <- found[1L]
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next
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}
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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])))
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if (length(found) > 0 & !is.na(found)) {
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x_new[i] <- found[1L]
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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])))
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if (length(found) > 0 & !is.na(found)) {
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x_new[i] <- found[1L]
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next
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}
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}
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if (!isFALSE(list(...)$initial_search)) {
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# transform back from other languages and try again
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x_translated <- paste(lapply(strsplit(x[i], "[^a-zA-Z0-9 ]"),
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function(y) {
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for (i in seq_len(length(y))) {
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y[i] <- ifelse(tolower(y[i]) %in% tolower(translations_file$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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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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if (!isFALSE(list(...)$initial_search2)) {
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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-zA-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, initial_search2 = 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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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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}
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}
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# not found
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x_unknown <- c(x_unknown, x_bak[x[i] == x_bak_clean][1])
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}
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# take failed ATC codes apart from rest
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x_unknown_ATCs <- x_unknown[x_unknown %like% "[A-Z][0-9][0-9][A-Z][A-Z][0-9][0-9]"]
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x_unknown <- x_unknown[!x_unknown %in% x_unknown_ATCs]
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if (length(x_unknown_ATCs) > 0) {
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warning("These ATC codes are not (yet) in the antibiotics data set: ",
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paste('"', sort(unique(x_unknown_ATCs)), '"', sep = "", collapse = ", "),
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".",
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call. = FALSE)
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}
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if (length(x_unknown) > 0) {
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warning("These values could not be coerced to a valid antimicrobial ID: ",
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paste('"', sort(unique(x_unknown)), '"', sep = "", collapse = ", "),
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".",
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call. = FALSE)
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}
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x_result <- data.frame(x = x_bak_clean, stringsAsFactors = FALSE) %>%
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left_join(data.frame(x = x, x_new = x_new, stringsAsFactors = FALSE), by = "x") %>%
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pull(x_new)
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if (length(x_result) == 0) {
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x_result <- NA_character_
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}
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structure(.Data = x_result,
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class = "ab")
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}
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#' @rdname as.ab
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#' @export
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is.ab <- function(x) {
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inherits(x, "ab")
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}
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#' @exportMethod print.ab
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#' @export
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#' @noRd
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print.ab <- function(x, ...) {
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cat("Class 'ab'\n")
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print(as.character(x), quote = FALSE)
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}
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#' @exportMethod as.data.frame.ab
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#' @export
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#' @noRd
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as.data.frame.ab <- function(x, ...) {
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# same as as.data.frame.character but with removed stringsAsFactors
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nm <- paste(deparse(substitute(x), width.cutoff = 500L),
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collapse = " ")
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if (!"nm" %in% names(list(...))) {
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as.data.frame.vector(x, ..., nm = nm)
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} else {
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as.data.frame.vector(x, ...)
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}
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}
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#' @exportMethod [.ab
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#' @export
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#' @noRd
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"[.ab" <- function(x, ...) {
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y <- NextMethod()
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attributes(y) <- attributes(x)
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y
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}
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#' @exportMethod [[.ab
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#' @export
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#' @noRd
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"[[.ab" <- function(x, ...) {
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y <- NextMethod()
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attributes(y) <- attributes(x)
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y
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}
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#' @exportMethod [<-.ab
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#' @export
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#' @noRd
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"[<-.ab" <- function(i, j, ..., value) {
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y <- NextMethod()
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attributes(y) <- attributes(i)
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class_integrity_check(y, "antimicrobial code", antibiotics$ab)
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}
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#' @exportMethod [[<-.ab
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#' @export
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#' @noRd
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"[[<-.ab" <- function(i, j, ..., value) {
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y <- NextMethod()
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attributes(y) <- attributes(i)
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class_integrity_check(y, "antimicrobial code", antibiotics$ab)
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}
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#' @exportMethod c.ab
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#' @export
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#' @noRd
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c.ab <- function(x, ...) {
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y <- NextMethod()
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attributes(y) <- attributes(x)
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class_integrity_check(y, "antimicrobial code", antibiotics$ab)
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}
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#' @importFrom pillar type_sum
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#' @export
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type_sum.ab <- function(x) {
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"ab"
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}
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#' @importFrom pillar pillar_shaft
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#' @export
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pillar_shaft.ab <- function(x, ...) {
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out <- format(x)
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out[is.na(x)] <- pillar::style_na("NA")
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pillar::new_pillar_shaft_simple(out, align = "left", min_width = 4)
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}
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