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436 lines
16 KiB
R
Executable File
436 lines
16 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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# AUTHORS #
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# Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
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# #
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# LICENCE #
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# This program is free software; you can redistribute it and/or modify #
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# it under the terms of the GNU General Public License version 2.0, #
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# as published by the Free Software Foundation. #
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# #
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# This program is distributed in the hope that it will be useful, #
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# but WITHOUT ANY WARRANTY; without even the implied warranty of #
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the #
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# GNU General Public License for more details. #
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# ==================================================================== #
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#' Determine multidrug-resistant organisms (MDRO)
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#'
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#' Determine which isolates are multidrug-resistant organisms (MDRO) according to country-specific guidelines.
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#' @param tbl table with antibiotic columns, like e.g. \code{amox} and \code{amcl}
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#' @param country country code to determine guidelines. EUCAST rules will be used when left empty, see Details. Should be or a code from the \href{https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2#Officially_assigned_code_elements}{list of ISO 3166-1 alpha-2 country codes}. Case-insensitive. Currently supported are \code{de} (Germany) and \code{nl} (the Netherlands).
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#' @param info print progress
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#' @inheritParams EUCAST_rules
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#' @param metr column name of an antibiotic. Use \code{NA} to skip a column, like \code{tica = NA}. Non-existing columns will anyway be skipped. See the Antibiotics section for an explanation of the abbreviations.
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#' @param ... parameters that are passed on to methods
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#' @inheritSection EUCAST_rules Antibiotics
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#' @details When \code{country} will be left blank, guidelines will be taken from EUCAST Expert Rules Version 3.1 "Intrinsic Resistance and Exceptional Phenotypes Tables" (\url{http://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf}).
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#' @return Ordered factor with levels \code{Unknown < Negative < Unconfirmed < Positive}.
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#' @rdname MDRO
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#' @importFrom dplyr %>%
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#' @importFrom crayon red blue
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#' @export
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#' @examples
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#' library(dplyr)
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#'
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#' septic_patients %>%
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#' mutate(EUCAST = MDRO(.),
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#' BRMO = BRMO(.))
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MDRO <- function(tbl,
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country = NULL,
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col_mo = NULL,
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info = TRUE,
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amcl = 'amcl',
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amik = 'amik',
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amox = 'amox',
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ampi = 'ampi',
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azit = 'azit',
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aztr = 'aztr',
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cefa = 'cefa',
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cfra = 'cfra',
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cfep = 'cfep',
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cfot = 'cfot',
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cfox = 'cfox',
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cfta = 'cfta',
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cftr = 'cftr',
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cfur = 'cfur',
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chlo = 'chlo',
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cipr = 'cipr',
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clar = 'clar',
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clin = 'clin',
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clox = 'clox',
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coli = 'coli',
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czol = 'czol',
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dapt = 'dapt',
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doxy = 'doxy',
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erta = 'erta',
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eryt = 'eryt',
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fosf = 'fosf',
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fusi = 'fusi',
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gent = 'gent',
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imip = 'imip',
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kana = 'kana',
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levo = 'levo',
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linc = 'linc',
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line = 'line',
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mero = 'mero',
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metr = 'metr',
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mino = 'mino',
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moxi = 'moxi',
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nali = 'nali',
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neom = 'neom',
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neti = 'neti',
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nitr = 'nitr',
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novo = 'novo',
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norf = 'norf',
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oflo = 'oflo',
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peni = 'peni',
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pita = 'pita',
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poly = 'poly',
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qida = 'qida',
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rifa = 'rifa',
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roxi = 'roxi',
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siso = 'siso',
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teic = 'teic',
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tetr = 'tetr',
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tica = 'tica',
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tige = 'tige',
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tobr = 'tobr',
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trim = 'trim',
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trsu = 'trsu',
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vanc = 'vanc',
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col_bactid = NULL) {
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if (!is.data.frame(tbl)) {
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stop("`tbl` must be a data frame.", call. = FALSE)
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}
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# try to find columns based on type
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# -- mo
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if (!is.null(col_bactid)) {
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col_mo <- col_bactid
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warning("Use of `col_bactid` is deprecated. Use `col_mo` instead.")
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} else if (is.null(col_mo) & "mo" %in% lapply(tbl, class)) {
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col_mo <- colnames(tbl)[lapply(tbl, class) == "mo"]
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message("NOTE: Using column `", col_mo, "` as input for `col_mo`.")
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} else if (!col_mo %in% colnames(tbl)) {
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stop('Column ', col_mo, ' not found.', call. = FALSE)
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}
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# strip whitespaces
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if (length(country) > 1) {
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stop('`country` must be a length one character string.', call. = FALSE)
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}
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if (is.null(country)) {
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country <- 'EUCAST'
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}
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country <- trimws(country)
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if (country != 'EUCAST' & !country %like% '^[a-z]{2}$') {
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stop('This is not a valid ISO 3166-1 alpha-2 country code: "', country, '". Please see ?MDRO.', call. = FALSE)
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}
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# create list and make country code case-independent
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guideline <- list(country = list(code = tolower(country)))
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if (guideline$country$code == 'eucast') {
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guideline$country$name <- '(European guidelines)'
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guideline$name <- 'EUCAST Expert Rules, "Intrinsic Resistance and Exceptional Phenotypes Tables"'
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guideline$version <- 'Version 3.1'
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guideline$source <- 'http://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf'
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# support per country:
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} else if (guideline$country$code == 'de') {
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guideline$country$name <- 'Germany'
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guideline$name <- ''
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guideline$version <- ''
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guideline$source <- ''
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} else if (guideline$country$code == 'nl') {
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guideline$country$name <- 'The Netherlands'
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guideline$name <- 'WIP-Richtlijn BRMO'
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guideline$version <- 'Revision of December 2017'
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guideline$source <- 'https://www.rivm.nl/Documenten_en_publicaties/Professioneel_Praktisch/Richtlijnen/Infectieziekten/WIP_Richtlijnen/WIP_Richtlijnen/Ziekenhuizen/WIP_richtlijn_BRMO_Bijzonder_Resistente_Micro_Organismen_ZKH'
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# add here more countries like this:
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# } else if (country$code == 'xx') {
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# country$name <- 'country name'
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} else {
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stop('This country code is currently unsupported: ', guideline$country$code, call. = FALSE)
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}
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if (info == TRUE) {
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cat("Determining multidrug-resistant organisms (MDRO), according to:\n",
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"Guideline: ", red(paste0(guideline$name, ", ", guideline$version, "\n")),
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"Country : ", red(paste0(guideline$country$name, "\n")),
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"Source : ", blue(paste0(guideline$source, "\n")),
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"\n", sep = "")
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}
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# check columns
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col.list <- c(amcl, amik, amox, ampi, azit, aztr, cefa, cfra, cfep, cfot,
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cfox, cfta, cftr, cfur, chlo, cipr, clar, clin, clox, coli,
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czol, dapt, doxy, erta, eryt, fosf, fusi, gent, imip, kana,
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levo, linc, line, mero, metr, mino, moxi, nali, neom, neti, nitr,
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novo, norf, oflo, peni, pita, poly, qida, rifa, roxi, siso,
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teic, tetr, tica, tige, tobr, trim, trsu, vanc)
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col.list <- check_available_columns(tbl = tbl, col.list = col.list, info = info)
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amcl <- col.list[amcl]
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amik <- col.list[amik]
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amox <- col.list[amox]
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ampi <- col.list[ampi]
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azit <- col.list[azit]
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aztr <- col.list[aztr]
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cefa <- col.list[cefa]
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cfra <- col.list[cfra]
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cfep <- col.list[cfep]
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cfot <- col.list[cfot]
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cfox <- col.list[cfox]
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cfta <- col.list[cfta]
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cftr <- col.list[cftr]
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cfur <- col.list[cfur]
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chlo <- col.list[chlo]
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cipr <- col.list[cipr]
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clar <- col.list[clar]
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clin <- col.list[clin]
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clox <- col.list[clox]
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coli <- col.list[coli]
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czol <- col.list[czol]
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dapt <- col.list[dapt]
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doxy <- col.list[doxy]
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erta <- col.list[erta]
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eryt <- col.list[eryt]
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fosf <- col.list[fosf]
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fusi <- col.list[fusi]
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gent <- col.list[gent]
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imip <- col.list[imip]
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kana <- col.list[kana]
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levo <- col.list[levo]
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linc <- col.list[linc]
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line <- col.list[line]
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mero <- col.list[mero]
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metr <- col.list[metr]
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mino <- col.list[mino]
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moxi <- col.list[moxi]
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nali <- col.list[nali]
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neom <- col.list[neom]
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neti <- col.list[neti]
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nitr <- col.list[nitr]
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novo <- col.list[novo]
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norf <- col.list[norf]
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oflo <- col.list[oflo]
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peni <- col.list[peni]
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pita <- col.list[pita]
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poly <- col.list[poly]
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qida <- col.list[qida]
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rifa <- col.list[rifa]
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roxi <- col.list[roxi]
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siso <- col.list[siso]
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teic <- col.list[teic]
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tetr <- col.list[tetr]
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tica <- col.list[tica]
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tige <- col.list[tige]
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tobr <- col.list[tobr]
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trim <- col.list[trim]
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trsu <- col.list[trsu]
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vanc <- col.list[vanc]
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# antibiotic classes
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aminoglycosides <- c(tobr, gent) # can also be kana but that one is often intrinsic R
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cephalosporins <- c(cfep, cfot, cfox, cfra, cfta, cftr, cfur, czol)
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cephalosporins_3rd <- c(cfot, cftr, cfta)
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carbapenems <- c(erta, imip, mero)
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fluoroquinolones <- c(oflo, cipr, levo, moxi)
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# helper function for editing the table
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trans_tbl <- function(to, rows, cols) {
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cols <- cols[!is.na(cols)]
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if (length(rows) > 0 & length(cols) > 0) {
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col_filter <- which(tbl[, cols] == 'R')
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rows <- rows[rows %in% col_filter]
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tbl[rows, 'MDRO'] <<- to
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}
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}
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if (!tbl %>% pull(col_mo) %>% is.mo()) {
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tbl[, col_mo] <- as.mo(tbl[, col_mo])
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}
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tbl <- tbl %>%
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# join to microorganisms data set
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left_join_microorganisms(by = col_mo) %>%
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# add unconfirmed to where genus is available
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mutate(MDRO = ifelse(!is.na(genus), 1, NA_integer_))
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if (guideline$country$code == 'eucast') {
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# EUCAST ------------------------------------------------------------------
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# Table 5
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trans_tbl(4,
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which(tbl$family == 'Enterobacteriaceae'
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| tbl$fullname %like% '^Pseudomonas aeruginosa'
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| tbl$genus == 'Acinetobacter'),
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coli)
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trans_tbl(4,
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which(tbl$fullname %like% '^Salmonella Typhi'),
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c(carbapenems, fluoroquinolones))
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trans_tbl(4,
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which(tbl$fullname %like% '^Haemophilus influenzae'),
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c(cephalosporins_3rd, carbapenems, fluoroquinolones))
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trans_tbl(4,
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which(tbl$fullname %like% '^Moraxella catarrhalis'),
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c(cephalosporins_3rd, fluoroquinolones))
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trans_tbl(4,
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which(tbl$fullname %like% '^Neisseria meningitidis'),
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c(cephalosporins_3rd, fluoroquinolones))
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trans_tbl(4,
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which(tbl$fullname %like% '^Neisseria gonorrhoeae'),
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azit)
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# Table 6
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trans_tbl(4,
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which(tbl$fullname %like% '^Staphylococcus (aureus|epidermidis|coagulase negatief|hominis|haemolyticus|intermedius|pseudointermedius)'),
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c(vanc, teic, dapt, line, qida, tige))
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trans_tbl(4,
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which(tbl$genus == 'Corynebacterium'),
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c(vanc, teic, dapt, line, qida, tige))
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trans_tbl(4,
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which(tbl$fullname %like% '^Streptococcus pneumoniae'),
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c(carbapenems, vanc, teic, dapt, line, qida, tige, rifa))
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trans_tbl(4, # Sr. groups A/B/C/G
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which(tbl$fullname %like% '^Streptococcus (pyogenes|agalactiae|equisimilis|equi|zooepidemicus|dysgalactiae|anginosus)'),
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c(peni, cephalosporins, vanc, teic, dapt, line, qida, tige))
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trans_tbl(4,
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which(tbl$genus == 'Enterococcus'),
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c(dapt, line, tige, teic))
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trans_tbl(4,
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which(tbl$fullname %like% '^Enterococcus faecalis'),
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c(ampi, amox))
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# Table 7
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trans_tbl(4,
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which(tbl$genus == 'Bacteroides'),
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metr)
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trans_tbl(4,
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which(tbl$fullname %like% '^Clostridium difficile'),
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c(metr, vanc))
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}
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if (guideline$country$code == 'de') {
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# Germany -----------------------------------------------------------------
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stop("We are still working on German guidelines in this beta version.", call. = FALSE)
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}
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if (guideline$country$code == 'nl') {
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# Netherlands -------------------------------------------------------------
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aminoglycosides <- aminoglycosides[!is.na(aminoglycosides)]
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fluoroquinolones <- fluoroquinolones[!is.na(fluoroquinolones)]
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carbapenems <- carbapenems[!is.na(carbapenems)]
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# Table 1
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tbl[which(
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tbl$family == 'Enterobacteriaceae'
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& rowSums(tbl[, aminoglycosides] == 'R', na.rm = TRUE) >= 1
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& rowSums(tbl[, fluoroquinolones] == 'R', na.rm = TRUE) >= 1
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), 'MDRO'] <- 4
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tbl[which(
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tbl$family == 'Enterobacteriaceae'
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& rowSums(tbl[, carbapenems] == 'R', na.rm = TRUE) >= 1
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), 'MDRO'] <- 3
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# rest is negative
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tbl[which(
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tbl$family == 'Enterobacteriaceae'
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& tbl$MDRO == 1
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), 'MDRO'] <- 2
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# Table 2
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tbl[which(
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tbl$genus == 'Acinetobacter'
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& rowSums(tbl[, carbapenems] == 'R', na.rm = TRUE) >= 1
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), 'MDRO'] <- 3
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tbl[which(
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tbl$genus == 'Acinetobacter'
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& rowSums(tbl[, aminoglycosides] == 'R', na.rm = TRUE) >= 1
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& rowSums(tbl[, fluoroquinolones] == 'R', na.rm = TRUE) >= 1
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), 'MDRO'] <- 4
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# rest of Acinetobacter is negative
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tbl[which(
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tbl$genus == 'Acinetobacter'
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& tbl$MDRO == 1
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), 'MDRO'] <- 2
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tbl[which(
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tbl$fullname %like% 'Stenotrophomonas maltophilia'
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& tbl[, trsu] == 'R'
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), 'MDRO'] <- 4
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# rest of Stenotrophomonas is negative
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tbl[which(
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tbl$fullname %like% 'Stenotrophomonas maltophilia'
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& tbl$MDRO == 1
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), 'MDRO'] <- 2
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tbl <- tbl %>% mutate(
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psae = 0,
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psae = ifelse(mero == "R" | imip == "R", psae + 1, psae),
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psae = ifelse(gent == "R" & tobr == "R", psae + 1, psae),
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psae = ifelse(cipr == "R", psae + 1, psae),
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psae = ifelse(cfta == "R", psae + 1, psae),
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psae = ifelse(pita == "R", psae + 1, psae),
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psae = ifelse(is.na(psae), 0, psae)
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)
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tbl[which(
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tbl$fullname %like% 'Pseudomonas aeruginosa'
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& tbl$psae >= 3
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), 'MDRO'] <- 4
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# rest of Pseudomonas is negative
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tbl[which(
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tbl$fullname %like% 'Pseudomonas aeruginosa'
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& tbl$MDRO == 1
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), 'MDRO'] <- 2
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# Table 3
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tbl[which(
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tbl$fullname %like% 'Streptococcus pneumoniae'
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& tbl[, peni] == 'R'
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), 'MDRO'] <- 4
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tbl[which(
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tbl$fullname %like% 'Streptococcus pneumoniae'
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& tbl[, vanc] == 'R'
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), 'MDRO'] <- 4
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# rest of Streptococcus pneumoniae is negative
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tbl[which(
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tbl$fullname %like% 'Streptococcus pneumoniae'
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& tbl$MDRO == 1
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), 'MDRO'] <- 2
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tbl[which(
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tbl$fullname %like% 'Enterococcus faecium'
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& rowSums(tbl[, c(peni, vanc)] == 'R', na.rm = TRUE) >= 1
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), 'MDRO'] <- 4
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# rest of Enterococcus faecium is negative
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tbl[which(
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tbl$fullname %like% 'Enterococcus faecium'
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& tbl$MDRO == 1
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), 'MDRO'] <- 2
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}
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factor(x = tbl$MDRO,
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levels = c(1:4),
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labels = c('Not evaluated', 'Negative', 'Unconfirmed', 'Positive'),
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ordered = TRUE)
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}
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#' @rdname MDRO
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#' @export
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BRMO <- function(tbl, country = "nl", ...) {
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MDRO(tbl = tbl, country = "nl", ...)
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}
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#' @rdname MDRO
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#' @export
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MRGN <- function(tbl, country = "de", ...) {
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MDRO(tbl = tbl, country = "de", ...)
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}
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#' @rdname MDRO
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#' @export
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EUCAST_exceptional_phenotypes <- function(tbl, country = "EUCAST", ...) {
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MDRO(tbl = tbl, country = "EUCAST", ...)
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}
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