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mdro and 1st isolate improvements

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dr. M.S. (Matthijs) Berends
2018-10-23 11:15:05 +02:00
parent 299c5bea43
commit 7997de6a6d
8 changed files with 138 additions and 95 deletions
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95
R/first_isolate.R
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@ -20,9 +20,9 @@
#'
#' Determine first (weighted) isolates of all microorganisms of every patient per episode and (if needed) per specimen type.
#' @param tbl a \code{data.frame} containing isolates.
#' @param col_date column name of the result date (or date that is was received on the lab)
#' @param col_patient_id column name of the unique IDs of the patients
#' @param col_mo column name of the unique IDs of the microorganisms, see \code{\link{mo}}. If this column has another class than \code{"mo"}, values will be coerced using \code{\link{as.mo}}.
#' @param col_date column name of the result date (or date that is was received on the lab), defaults to the first column of class \code{Date}
#' @param col_patient_id column name of the unique IDs of the patients, defaults to the first column that starts with 'patient' (case insensitive)
#' @param col_mo column name of the unique IDs of the microorganisms (see \code{\link{mo}}), defaults to the first column of class \code{mo}. If this column has another class than \code{"mo"}, values will be coerced using \code{\link{as.mo}}.
#' @param col_testcode column name of the test codes. Use \code{col_testcode = NA} to \strong{not} exclude certain test codes (like test codes for screening). In that case \code{testcodes_exclude} will be ignored. Supports tidyverse-like quotation.
#' @param col_specimen column name of the specimen type or group
#' @param col_icu column name of the logicals (\code{TRUE}/\code{FALSE}) whether a ward or department is an Intensive Care Unit (ICU)
@ -125,42 +125,63 @@
#' col_keyantibiotics = 'keyab')
#' }
first_isolate <- function(tbl,
col_date,
col_patient_id,
col_mo = NA,
col_testcode = NA,
col_specimen = NA,
col_icu = NA,
col_keyantibiotics = NA,
col_date = NULL,
col_patient_id = NULL,
col_mo = NULL,
col_testcode = NULL,
col_specimen = NULL,
col_icu = NULL,
col_keyantibiotics = NULL,
episode_days = 365,
testcodes_exclude = '',
testcodes_exclude = NULL,
icu_exclude = FALSE,
filter_specimen = NA,
filter_specimen = NULL,
output_logical = TRUE,
type = "keyantibiotics",
ignore_I = TRUE,
points_threshold = 2,
info = TRUE,
col_bactid = NA,
col_genus = NA,
col_species = NA) {
col_bactid = NULL,
col_genus = NULL,
col_species = NULL) {
if (!is.na(col_bactid)) {
if (!is.data.frame(tbl)) {
stop("`tbl` must be a data frame.", call. = FALSE)
}
# try to find columns based on type
# -- mo
if (!is.null(col_bactid)) {
col_mo <- col_bactid
warning("Use of `col_bactid` is deprecated. Use `col_mo` instead.")
} else if (is.null(col_mo) & "mo" %in% lapply(tbl, class)) {
col_mo <- colnames(tbl)[lapply(tbl, class) == "mo"]
message("NOTE: Using column `", col_mo, "` as input for `col_mo`.")
}
# -- date
if (is.null(col_date) & "Date" %in% lapply(tbl, class)) {
col_date <- colnames(tbl)[lapply(tbl, class) == "Date"]
message("NOTE: Using column `", col_date, "` as input for `col_date`.")
}
# -- patient id
if (is.null(col_patient_id) & any(colnames(tbl) %like% "^patient")) {
col_patient_id <- colnames(tbl)[colnames(tbl) %like% "^patient"][1]
message("NOTE: Using column `", col_patient_id, "` as input for `col_patient_id`.")
}
# bactid OR genus+species must be available
if (is.na(col_mo) & (is.na(col_genus) | is.na(col_species))) {
if (is.null(col_mo) & (is.null(col_genus) | is.null(col_species))) {
stop('`col_mo` or both `col_genus` and `col_species` must be available.')
}
# check if columns exist
check_columns_existance <- function(column, tblname = tbl) {
if (NROW(tblname) <= 1 | NCOL(tblname) <= 1) {
stop('Please check tbl for existance.')
}
if (!is.na(column)) {
if (!is.null(column)) {
if (!(column %in% colnames(tblname))) {
stop('Column `', column, '` not found.')
}
@ -176,7 +197,7 @@ first_isolate <- function(tbl,
check_columns_existance(col_icu)
check_columns_existance(col_keyantibiotics)
if (!is.na(col_mo)) {
if (!is.null(col_mo)) {
if (!tbl %>% pull(col_mo) %>% is.mo()) {
tbl[, col_mo] <- as.mo(tbl[, col_mo])
}
@ -186,41 +207,37 @@ first_isolate <- function(tbl,
col_species <- "species"
}
if (is.na(col_testcode)) {
testcodes_exclude <- NA
if (is.null(col_testcode)) {
testcodes_exclude <- NULL
}
# remove testcodes
if (!is.na(testcodes_exclude[1]) & testcodes_exclude[1] != '' & info == TRUE) {
if (!is.null(testcodes_exclude) & info == TRUE) {
cat('[Criteria] Excluded test codes:\n', toString(testcodes_exclude), '\n')
}
if (is.na(col_icu)) {
if (is.null(col_icu)) {
icu_exclude <- FALSE
} else {
tbl <- tbl %>%
mutate(col_icu = tbl %>% pull(col_icu) %>% as.logical())
}
if (is.na(col_specimen)) {
filter_specimen <- ''
if (is.null(col_specimen)) {
filter_specimen <- NULL
}
# filter on specimen group and keyantibiotics when they are filled in
if (!is.na(filter_specimen) & filter_specimen != '') {
if (!is.null(filter_specimen)) {
check_columns_existance(col_specimen, tbl)
if (info == TRUE) {
cat('[Criteria] Excluded other than specimen group \'', filter_specimen, '\'\n', sep = '')
}
} else {
filter_specimen <- ''
}
if (col_keyantibiotics %in% c(NA, '')) {
col_keyantibiotics <- ''
} else {
if (!is.null(col_keyantibiotics)) {
tbl <- tbl %>% mutate(key_ab = tbl %>% pull(col_keyantibiotics))
}
if (is.na(testcodes_exclude[1])) {
if (is.null(testcodes_exclude)) {
testcodes_exclude <- ''
}
@ -234,10 +251,10 @@ first_isolate <- function(tbl,
mutate(species = if_else(is.na(species) | species == "(no MO)", "", species),
genus = if_else(is.na(genus) | genus == "(no MO)", "", genus))
if (filter_specimen == '') {
if (is.null(filter_specimen)) {
# not filtering on specimen
if (icu_exclude == FALSE) {
if (info == TRUE & !is.na(col_icu)) {
if (info == TRUE & !is.null(col_icu)) {
cat('[Criteria] Included isolates from ICU.\n')
}
tbl <- tbl %>%
@ -267,9 +284,9 @@ first_isolate <- function(tbl,
}
} else {
# sort on specimen and only analyse these row to save time
# filtering on specimen and only analyse these row to save time
if (icu_exclude == FALSE) {
if (info == TRUE & !is.na(col_icu)) {
if (info == TRUE & !is.null(col_icu)) {
cat('[Criteria] Included isolates from ICU.\n')
}
tbl <- tbl %>%
@ -344,7 +361,7 @@ first_isolate <- function(tbl,
0))
weighted.notice <- ''
if (col_keyantibiotics != '') {
if (!is.null(col_keyantibiotics)) {
weighted.notice <- 'weighted '
if (info == TRUE) {
if (type == 'keyantibiotics') {
@ -402,7 +419,7 @@ first_isolate <- function(tbl,
# first one as TRUE
all_first[row.start, 'real_first_isolate'] <- TRUE
# no tests that should be included, or ICU
if (!is.na(col_testcode)) {
if (!is.null(col_testcode)) {
all_first[which(all_first[, col_testcode] %in% tolower(testcodes_exclude)), 'real_first_isolate'] <- FALSE
}
if (icu_exclude == TRUE) {

78
R/mdro.R
View File

@ -29,6 +29,8 @@
#' @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}).
#' @return Ordered factor with levels \code{Unknown < Negative < Unconfirmed < Positive}.
#' @rdname MDRO
#' @importFrom dplyr %>%
#' @importFrom crayon red blue
#' @export
#' @examples
#' library(dplyr)
@ -38,7 +40,7 @@
#' BRMO = BRMO(.))
MDRO <- function(tbl,
country = NULL,
col_mo = 'mo',
col_mo = NULL,
info = TRUE,
amcl = 'amcl',
amik = 'amik',
@ -99,13 +101,21 @@ MDRO <- function(tbl,
trim = 'trim',
trsu = 'trsu',
vanc = 'vanc',
col_bactid = 'bactid') {
col_bactid = NULL) {
if (col_bactid %in% colnames(tbl)) {
if (!is.data.frame(tbl)) {
stop("`tbl` must be a data frame.", call. = FALSE)
}
# try to find columns based on type
# -- mo
if (!is.null(col_bactid)) {
col_mo <- col_bactid
warning("Use of `col_bactid` is deprecated. Use `col_mo` instead.")
}
if (!col_mo %in% colnames(tbl)) {
} else if (is.null(col_mo) & "mo" %in% lapply(tbl, class)) {
col_mo <- colnames(tbl)[lapply(tbl, class) == "mo"]
message("NOTE: Using column `", col_mo, "` as input for `col_mo`.")
} else if (!col_mo %in% colnames(tbl)) {
stop('Column ', col_mo, ' not found.', call. = FALSE)
}
@ -142,23 +152,17 @@ MDRO <- function(tbl,
guideline$version <- 'Revision of December 2017'
guideline$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'
# add here more countries like this:
# } else if (country$code == 'AA') {
# } else if (country$code == 'xx') {
# country$name <- 'country name'
} else {
stop('This country code is currently unsupported: ', guideline$country$code, call. = FALSE)
}
# Console colours
# source: http://www.tldp.org/HOWTO/Bash-Prompt-HOWTO/x329.html
ANSI_red <- "\033[31m"
ANSI_blue <- "\033[34m"
ANSI_reset <- "\033[0m"
if (info == TRUE) {
cat("Determining multidrug-resistant organisms (MDRO), according to:\n",
"Guideline: ", ANSI_red, guideline$name, ", ", guideline$version, ANSI_reset, "\n",
"Country : ", ANSI_red, guideline$country$name, ANSI_reset, "\n",
"Source : ", ANSI_blue, guideline$source, ANSI_reset, "\n",
"Guideline: ", red(paste0(guideline$name, ", ", guideline$version, "\n")),
"Country : ", red(paste0(guideline$country$name, "\n")),
"Source : ", blue(paste0(guideline$source, "\n")),
"\n", sep = "")
}
@ -231,18 +235,11 @@ MDRO <- function(tbl,
vanc <- col.list[vanc]
# antibiotic classes
aminoglycosides <- c(tobr, gent, kana, neom, neti, siso)
tetracyclines <- c(doxy, mino, tetr) # since EUCAST v3.1 tige(cycline) is set apart
polymyxins <- c(poly, coli)
macrolides <- c(eryt, azit, roxi, clar) # since EUCAST v3.1 clin(damycin) is set apart
glycopeptides <- c(vanc, teic)
streptogramins <- qida # should officially also be pristinamycin and quinupristin/dalfopristin
aminoglycosides <- c(tobr, gent) # can also be kana but that one is often intrinsic R
cephalosporins <- c(cfep, cfot, cfox, cfra, cfta, cftr, cfur, czol)
cephalosporins_3rd <- c(cfot, cftr, cfta)
carbapenems <- c(erta, imip, mero)
aminopenicillins <- c(ampi, amox)
ureidopenicillins <- pita # should officially also be azlo and mezlo
fluoroquinolones <- c(oflo, cipr, norf, levo, moxi)
fluoroquinolones <- c(oflo, cipr, levo, moxi)
# helper function for editing the table
trans_tbl <- function(to, rows, cols) {
@ -254,10 +251,15 @@ MDRO <- function(tbl,
}
}
# join microorganisms
tbl <- tbl %>% left_join_microorganisms(col_mo)
if (!tbl %>% pull(col_mo) %>% is.mo()) {
tbl[, col_mo] <- as.mo(tbl[, col_mo])
}
tbl$MDRO <- NA_integer_
tbl <- tbl %>%
# join to microorganisms data set
left_join_microorganisms(by = col_mo) %>%
# add unconfirmed to where genus is available
mutate(MDRO = ifelse(!is.na(genus), 1, NA_integer_))
if (guideline$country$code == 'eucast') {
# EUCAST ------------------------------------------------------------------
@ -327,6 +329,11 @@ MDRO <- function(tbl,
& rowSums(tbl[, aminoglycosides] == 'R', na.rm = TRUE) >= 1
& rowSums(tbl[, fluoroquinolones] == 'R', na.rm = TRUE) >= 1
), 'MDRO'] <- 4
a <<- tbl[which(
tbl$family == 'Enterobacteriaceae'
& rowSums(tbl[, aminoglycosides] == 'R', na.rm = TRUE) >= 1
& rowSums(tbl[, fluoroquinolones] == 'R', na.rm = TRUE) >= 1
), ]
tbl[which(
tbl$family == 'Enterobacteriaceae'
& rowSums(tbl[, carbapenems] == 'R', na.rm = TRUE) >= 1
@ -363,13 +370,18 @@ MDRO <- function(tbl,
& tbl$MDRO == 1
), 'MDRO'] <- 2
tbl <- tbl %>% mutate(
psae = 0,
psae = ifelse(mero == "R" | imip == "R", psae + 1, psae),
psae = ifelse(gent == "R" & tobr == "R", psae + 1, psae),
psae = ifelse(cipr == "R", psae + 1, psae),
psae = ifelse(cfta == "R", psae + 1, psae),
psae = ifelse(pita == "R", psae + 1, psae),
psae = ifelse(is.na(psae), 0, psae)
)
tbl[which(
tbl$fullname %like% 'Pseudomonas aeruginosa'
& sum(rowSums(tbl[, carbapenems] == 'R', na.rm = TRUE) >= 1,
rowSums(tbl[, aminoglycosides] == 'R', na.rm = TRUE) >= 1,
rowSums(tbl[, fluoroquinolones] == 'R', na.rm = TRUE) >= 1,
tbl[, cfta] == 'R',
tbl[, pita] == 'R') >= 3
& tbl$psae >= 3
), 'MDRO'] <- 4
# rest of Pseudomonas is negative
tbl[which(
@ -405,7 +417,7 @@ MDRO <- function(tbl,
factor(x = tbl$MDRO,
levels = c(1:4),
labels = c('Unknown', 'Negative', 'Unconfirmed', 'Positive'),
labels = c('Not evaluated', 'Negative', 'Unconfirmed', 'Positive'),
ordered = TRUE)
}