mirror of
https://github.com/msberends/AMR.git
synced 2024-12-25 18:06:12 +01:00
367 lines
17 KiB
R
Executable File
367 lines
17 KiB
R
Executable File
# ==================================================================== #
|
|
# TITLE #
|
|
# Antimicrobial Resistance (AMR) Analysis for R #
|
|
# #
|
|
# SOURCE #
|
|
# https://github.com/msberends/AMR #
|
|
# #
|
|
# LICENCE #
|
|
# (c) 2018-2020 Berends MS, Luz CF et al. #
|
|
# Developed at the University of Groningen, the Netherlands, in #
|
|
# collaboration with non-profit organisations Certe Medical #
|
|
# Diagnostics & Advice, and University Medical Center Groningen. #
|
|
# #
|
|
# This R package is free software; you can freely use and distribute #
|
|
# it for both personal and commercial purposes under the terms of the #
|
|
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
|
|
# the Free Software Foundation. #
|
|
# We created this package for both routine data analysis and academic #
|
|
# research and it was publicly released in the hope that it will be #
|
|
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
|
|
# #
|
|
# Visit our website for the full manual and a complete tutorial about #
|
|
# how to conduct AMR analysis: https://msberends.github.io/AMR/ #
|
|
# ==================================================================== #
|
|
|
|
#' Key antibiotics for first *weighted* isolates
|
|
#'
|
|
#' These function can be used to determine first isolates (see [first_isolate()]). Using key antibiotics to determine first isolates is more reliable than without key antibiotics. These selected isolates will then be called first *weighted* isolates.
|
|
#' @inheritSection lifecycle Stable lifecycle
|
|
#' @param x a data.frame with antibiotics columns, like `AMX` or `amox`
|
|
#' @param y,z character vectors to compare
|
|
#' @inheritParams first_isolate
|
|
#' @param universal_1,universal_2,universal_3,universal_4,universal_5,universal_6 column names of **broad-spectrum** antibiotics, case-insensitive. See details for which antibiotics will be used at default (which are guessed with [guess_ab_col()]).
|
|
#' @param GramPos_1,GramPos_2,GramPos_3,GramPos_4,GramPos_5,GramPos_6 column names of antibiotics for **Gram-positives**, case-insensitive. See details for which antibiotics will be used at default (which are guessed with [guess_ab_col()]).
|
|
#' @param GramNeg_1,GramNeg_2,GramNeg_3,GramNeg_4,GramNeg_5,GramNeg_6 column names of antibiotics for **Gram-negatives**, case-insensitive. See details for which antibiotics will be used at default (which are guessed with [guess_ab_col()]).
|
|
#' @param warnings give a warning about missing antibiotic columns (they will be ignored)
|
|
#' @param ... other parameters passed on to functions
|
|
#' @details The function [key_antibiotics()] returns a character vector with 12 antibiotic results for every isolate. These isolates can then be compared using [key_antibiotics_equal()], to check if two isolates have generally the same antibiogram. Missing and invalid values are replaced with a dot (`"."`) by [key_antibiotics()] and ignored by [key_antibiotics_equal()].
|
|
#'
|
|
#' The [first_isolate()] function only uses this function on the same microbial species from the same patient. Using this, e.g. an MRSA will be included after a susceptible *S. aureus* (MSSA) is found within the same patient episode. Without key antibiotic comparison it would not. See [first_isolate()] for more info.
|
|
#'
|
|
#' At default, the antibiotics that are used for **Gram-positive bacteria** are:
|
|
#' - Amoxicillin
|
|
#' - Amoxicillin/clavulanic acid
|
|
#' - Cefuroxime
|
|
#' - Piperacillin/tazobactam
|
|
#' - Ciprofloxacin
|
|
#' - Trimethoprim/sulfamethoxazole
|
|
#' - Vancomycin
|
|
#' - Teicoplanin
|
|
#' - Tetracycline
|
|
#' - Erythromycin
|
|
#' - Oxacillin
|
|
#' - Rifampin
|
|
#'
|
|
#' At default the antibiotics that are used for **Gram-negative bacteria** are:
|
|
#' - Amoxicillin
|
|
#' - Amoxicillin/clavulanic acid
|
|
#' - Cefuroxime
|
|
#' - Piperacillin/tazobactam
|
|
#' - Ciprofloxacin
|
|
#' - Trimethoprim/sulfamethoxazole
|
|
#' - Gentamicin
|
|
#' - Tobramycin
|
|
#' - Colistin
|
|
#' - Cefotaxime
|
|
#' - Ceftazidime
|
|
#' - Meropenem
|
|
#'
|
|
#' The function [key_antibiotics_equal()] checks the characters returned by [key_antibiotics()] for equality, and returns a [`logical`] vector.
|
|
#' @inheritSection first_isolate Key antibiotics
|
|
#' @rdname key_antibiotics
|
|
#' @export
|
|
#' @seealso [first_isolate()]
|
|
#' @inheritSection AMR Read more on our website!
|
|
#' @examples
|
|
#' # `example_isolates` is a dataset available in the AMR package.
|
|
#' # See ?example_isolates.
|
|
#'
|
|
#' # output of the `key_antibiotics` function could be like this:
|
|
#' strainA <- "SSSRR.S.R..S"
|
|
#' strainB <- "SSSIRSSSRSSS"
|
|
#'
|
|
#' # can those strings can be compared with:
|
|
#' key_antibiotics_equal(strainA, strainB)
|
|
#' # TRUE, because I is ignored (as well as missing values)
|
|
#'
|
|
#' key_antibiotics_equal(strainA, strainB, ignore_I = FALSE)
|
|
#' # FALSE, because I is not ignored and so the 4th value differs
|
|
#'
|
|
#' \donttest{
|
|
#' if (require("dplyr")) {
|
|
#' # set key antibiotics to a new variable
|
|
#' my_patients <- example_isolates %>%
|
|
#' mutate(keyab = key_antibiotics(.)) %>%
|
|
#' mutate(
|
|
#' # now calculate first isolates
|
|
#' first_regular = first_isolate(., col_keyantibiotics = FALSE),
|
|
#' # and first WEIGHTED isolates
|
|
#' first_weighted = first_isolate(., col_keyantibiotics = "keyab")
|
|
#' )
|
|
#'
|
|
#' # Check the difference, in this data set it results in 7% more isolates:
|
|
#' sum(my_patients$first_regular, na.rm = TRUE)
|
|
#' sum(my_patients$first_weighted, na.rm = TRUE)
|
|
#' }
|
|
#' }
|
|
key_antibiotics <- function(x,
|
|
col_mo = NULL,
|
|
universal_1 = guess_ab_col(x, "amoxicillin"),
|
|
universal_2 = guess_ab_col(x, "amoxicillin/clavulanic acid"),
|
|
universal_3 = guess_ab_col(x, "cefuroxime"),
|
|
universal_4 = guess_ab_col(x, "piperacillin/tazobactam"),
|
|
universal_5 = guess_ab_col(x, "ciprofloxacin"),
|
|
universal_6 = guess_ab_col(x, "trimethoprim/sulfamethoxazole"),
|
|
GramPos_1 = guess_ab_col(x, "vancomycin"),
|
|
GramPos_2 = guess_ab_col(x, "teicoplanin"),
|
|
GramPos_3 = guess_ab_col(x, "tetracycline"),
|
|
GramPos_4 = guess_ab_col(x, "erythromycin"),
|
|
GramPos_5 = guess_ab_col(x, "oxacillin"),
|
|
GramPos_6 = guess_ab_col(x, "rifampin"),
|
|
GramNeg_1 = guess_ab_col(x, "gentamicin"),
|
|
GramNeg_2 = guess_ab_col(x, "tobramycin"),
|
|
GramNeg_3 = guess_ab_col(x, "colistin"),
|
|
GramNeg_4 = guess_ab_col(x, "cefotaxime"),
|
|
GramNeg_5 = guess_ab_col(x, "ceftazidime"),
|
|
GramNeg_6 = guess_ab_col(x, "meropenem"),
|
|
warnings = TRUE,
|
|
...) {
|
|
meet_criteria(x, allow_class = "data.frame")
|
|
meet_criteria(col_mo, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
|
|
meet_criteria(universal_1, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
|
|
meet_criteria(universal_2, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
|
|
meet_criteria(universal_3, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
|
|
meet_criteria(universal_4, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
|
|
meet_criteria(universal_5, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
|
|
meet_criteria(universal_6, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
|
|
meet_criteria(GramPos_1, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
|
|
meet_criteria(GramPos_2, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
|
|
meet_criteria(GramPos_3, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
|
|
meet_criteria(GramPos_4, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
|
|
meet_criteria(GramPos_5, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
|
|
meet_criteria(GramPos_6, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
|
|
meet_criteria(GramNeg_1, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
|
|
meet_criteria(GramNeg_2, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
|
|
meet_criteria(GramNeg_3, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
|
|
meet_criteria(GramNeg_4, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
|
|
meet_criteria(GramNeg_5, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
|
|
meet_criteria(GramNeg_6, allow_class = "character", has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
|
|
meet_criteria(warnings, allow_class = "logical", has_length = 1)
|
|
|
|
dots <- unlist(list(...))
|
|
if (length(dots) != 0) {
|
|
# backwards compatibility with old parameters
|
|
dots.names <- dots %pm>% names()
|
|
if ("info" %in% dots.names) {
|
|
warnings <- dots[which(dots.names == "info")]
|
|
}
|
|
}
|
|
|
|
# try to find columns based on type
|
|
# -- mo
|
|
if (is.null(col_mo)) {
|
|
col_mo <- search_type_in_df(x = x, type = "mo")
|
|
}
|
|
stop_if(is.null(col_mo), "`col_mo` must be set")
|
|
|
|
# check columns
|
|
col.list <- c(universal_1, universal_2, universal_3, universal_4, universal_5, universal_6,
|
|
GramPos_1, GramPos_2, GramPos_3, GramPos_4, GramPos_5, GramPos_6,
|
|
GramNeg_1, GramNeg_2, GramNeg_3, GramNeg_4, GramNeg_5, GramNeg_6)
|
|
check_available_columns <- function(x, col.list, warnings = TRUE) {
|
|
# check columns
|
|
col.list <- col.list[!is.na(col.list) & !is.null(col.list)]
|
|
names(col.list) <- col.list
|
|
col.list.bak <- col.list
|
|
# are they available as upper case or lower case then?
|
|
for (i in seq_len(length(col.list))) {
|
|
if (is.null(col.list[i]) | isTRUE(is.na(col.list[i]))) {
|
|
col.list[i] <- NA
|
|
} else if (toupper(col.list[i]) %in% colnames(x)) {
|
|
col.list[i] <- toupper(col.list[i])
|
|
} else if (tolower(col.list[i]) %in% colnames(x)) {
|
|
col.list[i] <- tolower(col.list[i])
|
|
} else if (!col.list[i] %in% colnames(x)) {
|
|
col.list[i] <- NA
|
|
}
|
|
}
|
|
if (!all(col.list %in% colnames(x))) {
|
|
if (warnings == TRUE) {
|
|
warning_("Some columns do not exist and will be ignored: ",
|
|
col.list.bak[!(col.list %in% colnames(x))] %pm>% toString(),
|
|
".\nTHIS MAY STRONGLY INFLUENCE THE OUTCOME.",
|
|
immediate = TRUE,
|
|
call = FALSE)
|
|
}
|
|
}
|
|
col.list
|
|
}
|
|
|
|
col.list <- check_available_columns(x = x, col.list = col.list, warnings = warnings)
|
|
universal_1 <- col.list[universal_1]
|
|
universal_2 <- col.list[universal_2]
|
|
universal_3 <- col.list[universal_3]
|
|
universal_4 <- col.list[universal_4]
|
|
universal_5 <- col.list[universal_5]
|
|
universal_6 <- col.list[universal_6]
|
|
GramPos_1 <- col.list[GramPos_1]
|
|
GramPos_2 <- col.list[GramPos_2]
|
|
GramPos_3 <- col.list[GramPos_3]
|
|
GramPos_4 <- col.list[GramPos_4]
|
|
GramPos_5 <- col.list[GramPos_5]
|
|
GramPos_6 <- col.list[GramPos_6]
|
|
GramNeg_1 <- col.list[GramNeg_1]
|
|
GramNeg_2 <- col.list[GramNeg_2]
|
|
GramNeg_3 <- col.list[GramNeg_3]
|
|
GramNeg_4 <- col.list[GramNeg_4]
|
|
GramNeg_5 <- col.list[GramNeg_5]
|
|
GramNeg_6 <- col.list[GramNeg_6]
|
|
|
|
universal <- c(universal_1, universal_2, universal_3,
|
|
universal_4, universal_5, universal_6)
|
|
|
|
gram_positive <- c(universal,
|
|
GramPos_1, GramPos_2, GramPos_3,
|
|
GramPos_4, GramPos_5, GramPos_6)
|
|
gram_positive <- gram_positive[!is.null(gram_positive)]
|
|
gram_positive <- gram_positive[!is.na(gram_positive)]
|
|
if (length(gram_positive) < 12) {
|
|
warning_("Only using ", length(gram_positive), " different antibiotics as key antibiotics for Gram-positives. See ?key_antibiotics.", call = FALSE)
|
|
}
|
|
|
|
gram_negative <- c(universal,
|
|
GramNeg_1, GramNeg_2, GramNeg_3,
|
|
GramNeg_4, GramNeg_5, GramNeg_6)
|
|
gram_negative <- gram_negative[!is.null(gram_negative)]
|
|
gram_negative <- gram_negative[!is.na(gram_negative)]
|
|
if (length(gram_negative) < 12) {
|
|
warning_("Only using ", length(gram_negative), " different antibiotics as key antibiotics for Gram-negatives. See ?key_antibiotics.", call = FALSE)
|
|
}
|
|
|
|
x <- as.data.frame(x, stringsAsFactors = FALSE)
|
|
x[, col_mo] <- as.mo(x[, col_mo, drop = TRUE])
|
|
x$gramstain <- mo_gramstain(x[, col_mo, drop = TRUE], language = NULL)
|
|
x$key_ab <- NA_character_
|
|
|
|
# Gram +
|
|
x$key_ab <- pm_if_else(x$gramstain == "Gram-positive",
|
|
tryCatch(apply(X = x[, gram_positive],
|
|
MARGIN = 1,
|
|
FUN = function(x) paste(x, collapse = "")),
|
|
error = function(e) paste0(rep(".", 12), collapse = "")),
|
|
x$key_ab)
|
|
|
|
# Gram -
|
|
x$key_ab <- pm_if_else(x$gramstain == "Gram-negative",
|
|
tryCatch(apply(X = x[, gram_negative],
|
|
MARGIN = 1,
|
|
FUN = function(x) paste(x, collapse = "")),
|
|
error = function(e) paste0(rep(".", 12), collapse = "")),
|
|
x$key_ab)
|
|
|
|
# format
|
|
key_abs <- toupper(gsub("[^SIR]", ".", gsub("(NA|NULL)", ".", x$key_ab)))
|
|
|
|
if (pm_n_distinct(key_abs) == 1) {
|
|
warning_("No distinct key antibiotics determined.", call = FALSE)
|
|
}
|
|
|
|
key_abs
|
|
|
|
}
|
|
|
|
#' @rdname key_antibiotics
|
|
#' @export
|
|
key_antibiotics_equal <- function(y,
|
|
z,
|
|
type = c("keyantibiotics", "points"),
|
|
ignore_I = TRUE,
|
|
points_threshold = 2,
|
|
info = FALSE) {
|
|
meet_criteria(y, allow_class = "character")
|
|
meet_criteria(z, allow_class = "character")
|
|
meet_criteria(type, allow_class = "character", has_length = c(1, 2))
|
|
meet_criteria(ignore_I, allow_class = "logical", has_length = 1)
|
|
meet_criteria(points_threshold, allow_class = c("numeric", "integer"), has_length = 1)
|
|
meet_criteria(info, allow_class = "logical", has_length = 1)
|
|
|
|
stop_ifnot(length(y) == length(z), "length of `y` and `z` must be equal")
|
|
# y is active row, z is lag
|
|
x <- y
|
|
y <- z
|
|
|
|
type <- type[1]
|
|
|
|
# only show progress bar on points or when at least 5000 isolates
|
|
info_needed <- info == TRUE & (type == "points" | length(x) > 5000)
|
|
|
|
result <- logical(length(x))
|
|
|
|
if (info_needed == TRUE) {
|
|
p <- progress_ticker(length(x))
|
|
on.exit(close(p))
|
|
}
|
|
|
|
for (i in seq_len(length(x))) {
|
|
|
|
if (info_needed == TRUE) {
|
|
p$tick()
|
|
}
|
|
|
|
if (is.na(x[i])) {
|
|
x[i] <- ""
|
|
}
|
|
if (is.na(y[i])) {
|
|
y[i] <- ""
|
|
}
|
|
|
|
if (x[i] == y[i]) {
|
|
|
|
result[i] <- TRUE
|
|
|
|
} else if (nchar(x[i]) != nchar(y[i])) {
|
|
|
|
result[i] <- FALSE
|
|
|
|
} else {
|
|
|
|
x_split <- strsplit(x[i], "")[[1]]
|
|
y_split <- strsplit(y[i], "")[[1]]
|
|
|
|
if (type == "keyantibiotics") {
|
|
|
|
if (ignore_I == TRUE) {
|
|
x_split[x_split == "I"] <- "."
|
|
y_split[y_split == "I"] <- "."
|
|
}
|
|
|
|
y_split[x_split == "."] <- "."
|
|
x_split[y_split == "."] <- "."
|
|
|
|
result[i] <- all(x_split == y_split)
|
|
|
|
} else if (type == "points") {
|
|
# count points for every single character:
|
|
# - no change is 0 points
|
|
# - I <-> S|R is 0.5 point
|
|
# - S|R <-> R|S is 1 point
|
|
# use the levels of as.rsi (S = 1, I = 2, R = 3)
|
|
|
|
suppressWarnings(x_split <- x_split %pm>% as.rsi() %pm>% as.double())
|
|
suppressWarnings(y_split <- y_split %pm>% as.rsi() %pm>% as.double())
|
|
|
|
points <- (x_split - y_split) %pm>% abs() %pm>% sum(na.rm = TRUE) / 2
|
|
result[i] <- points >= points_threshold
|
|
|
|
} else {
|
|
stop("`", type, '` is not a valid value for type, must be "points" or "keyantibiotics". See ?key_antibiotics')
|
|
}
|
|
}
|
|
}
|
|
if (info_needed == TRUE) {
|
|
close(p)
|
|
}
|
|
result
|
|
}
|