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Replace RSI with SIR

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This commit is contained in:
Dr. Matthijs Berends
2023-01-21 23:47:20 +01:00
committed by GitHub
parent 24b12024ce
commit 98e62c9af2
127 changed files with 1746 additions and 1648 deletions
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26
R/first_isolate.R
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@ -48,7 +48,7 @@
#' @param points_threshold minimum number of points to require before differences in the antibiogram will lead to inclusion of an isolate when `type = "points"`, see *Details*
#' @param info a [logical] to indicate info should be printed, defaults to `TRUE` only in interactive mode
#' @param include_unknown a [logical] to indicate whether 'unknown' microorganisms should be included too, i.e. microbial code `"UNKNOWN"`, which defaults to `FALSE`. For WHONET users, this means that all records with organism code `"con"` (*contamination*) will be excluded at default. Isolates with a microbial ID of `NA` will always be excluded as first isolate.
#' @param include_untested_rsi a [logical] to indicate whether also rows without antibiotic results are still eligible for becoming a first isolate. Use `include_untested_rsi = FALSE` to always return `FALSE` for such rows. This checks the data set for columns of class `rsi` and consequently requires transforming columns with antibiotic results using [as.rsi()] first.
#' @param include_untested_sir a [logical] to indicate whether also rows without antibiotic results are still eligible for becoming a first isolate. Use `include_untested_sir = FALSE` to always return `FALSE` for such rows. This checks the data set for columns of class `sir` and consequently requires transforming columns with antibiotic results using [as.sir()] first.
#' @param ... arguments passed on to [first_isolate()] when using [filter_first_isolate()], otherwise arguments passed on to [key_antimicrobials()] (such as `universal`, `gram_negative`, `gram_positive`)
#' @details
#' To conduct epidemiological analyses on antimicrobial resistance data, only so-called first isolates should be included to prevent overestimation and underestimation of antimicrobial resistance. Different methods can be used to do so, see below.
@ -176,7 +176,7 @@ first_isolate <- function(x = NULL,
points_threshold = 2,
info = interactive(),
include_unknown = FALSE,
include_untested_rsi = TRUE,
include_untested_sir = TRUE,
...) {
if (is_null_or_grouped_tbl(x)) {
# when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
@ -228,19 +228,19 @@ first_isolate <- function(x = NULL,
meet_criteria(points_threshold, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
meet_criteria(info, allow_class = "logical", has_length = 1)
meet_criteria(include_unknown, allow_class = "logical", has_length = 1)
meet_criteria(include_untested_rsi, allow_class = "logical", has_length = 1)
meet_criteria(include_untested_sir, allow_class = "logical", has_length = 1)
# remove data.table, grouping from tibbles, etc.
x <- as.data.frame(x, stringsAsFactors = FALSE)
any_col_contains_rsi <- any(vapply(
any_col_contains_sir <- any(vapply(
FUN.VALUE = logical(1),
X = x,
# check only first 10,000 rows
FUN = function(x) any(as.character(x[1:10000]) %in% c("R", "S", "I"), na.rm = TRUE),
FUN = function(x) any(as.character(x[1:10000]) %in% c("S", "I", "R"), na.rm = TRUE),
USE.NAMES = FALSE
))
if (method == "phenotype-based" && !any_col_contains_rsi) {
if (method == "phenotype-based" && !any_col_contains_sir) {
method <- "episode-based"
}
if (isTRUE(info) && message_not_thrown_before("first_isolate", "method")) {
@ -285,13 +285,13 @@ first_isolate <- function(x = NULL,
type <- "keyantimicrobials"
}
if (type == "points") {
x$keyantimicrobials <- all_antimicrobials(x, only_rsi_columns = FALSE)
x$keyantimicrobials <- all_antimicrobials(x, only_sir_columns = FALSE)
col_keyantimicrobials <- "keyantimicrobials"
} else if (type == "keyantimicrobials" && is.null(col_keyantimicrobials)) {
col_keyantimicrobials <- search_type_in_df(x = x, type = "keyantimicrobials", info = info)
if (is.null(col_keyantimicrobials)) {
# still not found as a column, create it ourselves
x$keyantimicrobials <- key_antimicrobials(x, only_rsi_columns = FALSE, col_mo = col_mo, ...)
x$keyantimicrobials <- key_antimicrobials(x, only_sir_columns = FALSE, col_mo = col_mo, ...)
col_keyantimicrobials <- "keyantimicrobials"
}
}
@ -581,13 +581,13 @@ first_isolate <- function(x = NULL,
x[which(is.na(x$newvar_mo)), "newvar_first_isolate"] <- FALSE
# handle isolates without antibiogram
if (include_untested_rsi == FALSE && any(is.rsi(x))) {
rsi_all_NA <- which(unname(vapply(
if (include_untested_sir == FALSE && any(is.sir(x))) {
sir_all_NA <- which(unname(vapply(
FUN.VALUE = logical(1),
as.data.frame(t(x[, is.rsi(x), drop = FALSE])),
function(rsi_values) all(is.na(rsi_values))
as.data.frame(t(x[, is.sir(x), drop = FALSE])),
function(sir_values) all(is.na(sir_values))
)))
x[rsi_all_NA, "newvar_first_isolate"] <- FALSE
x[sir_all_NA, "newvar_first_isolate"] <- FALSE
}
# arrange back according to original sorting again