mirror of
https://github.com/msberends/AMR.git
synced 2025-07-09 01:22:25 +02:00
rsi family for resistance analysis
This commit is contained in:
@ -5,6 +5,10 @@ rsi_calc_S <- function(x, include_I) {
|
||||
.Call(`_AMR_rsi_calc_S`, x, include_I)
|
||||
}
|
||||
|
||||
rsi_calc_I <- function(x) {
|
||||
.Call(`_AMR_rsi_calc_I`, x)
|
||||
}
|
||||
|
||||
rsi_calc_R <- function(x, include_I) {
|
||||
.Call(`_AMR_rsi_calc_R`, x, include_I)
|
||||
}
|
||||
|
||||
@ -23,6 +23,7 @@
|
||||
#' @param Becker a logical to indicate whether \emph{Staphylococci} should be categorised into Coagulase Negative \emph{Staphylococci} ("CoNS") and Coagulase Positive \emph{Staphylococci} ("CoPS") instead of their own species, according to Karsten Becker \emph{et al.} [1]. This excludes \emph{Staphylococcus aureus} at default, use \code{Becker = "all"} to also categorise \emph{S. aureus} as "CoPS".
|
||||
#' @param Lancefield a logical to indicate whether beta-haemolytic \emph{Streptococci} should be categorised into Lancefield groups instead of their own species, according to Rebecca C. Lancefield [2]. These \emph{Streptococci} will be categorised in their first group, i.e. \emph{Streptococcus dysgalactiae} will be group C, although officially it was also categorised into groups G and L. Groups D and E will be ignored, since they are \emph{Enterococci}.
|
||||
#' @rdname as.bactid
|
||||
#' @keywords bactid Becker becker Lancefield lancefield guess
|
||||
#' @details \code{guess_bactid} is an alias of \code{as.bactid}.
|
||||
#'
|
||||
#' Some exceptions have been built in to get more logical results, based on prevalence of human pathogens. These are:
|
||||
|
||||
@ -18,20 +18,17 @@
|
||||
|
||||
#' Calculate resistance of isolates
|
||||
#'
|
||||
#' These functions can be used to calculate the (co-)resistance of microbial isolates (i.e. percentage S, SI, IR or R). All functions can be used in \code{dplyr}s \code{\link[dplyr]{summarise}} and support grouped variables, see \emph{Examples}. \cr\cr
|
||||
#' \code{R} and \code{IR} can be used to calculate resistance, \code{S} and \code{SI} can be used to calculate susceptibility.\cr
|
||||
#' \code{n_rsi} counts all cases where antimicrobial interpretations are available.
|
||||
#' These functions can be used to calculate the (co-)resistance of microbial isolates (i.e. percentage S, SI, I, IR or R). All functions can be used in \code{dplyr}s \code{\link[dplyr]{summarise}} and support grouped variables, see \emph{Examples}. \cr\cr
|
||||
#' \code{rsi_R} and \code{rsi_IR} can be used to calculate resistance, \code{rsi_S} and \code{rsi_SI} can be used to calculate susceptibility.\cr
|
||||
#' \code{rsi_n} counts all cases where antimicrobial interpretations are available.
|
||||
#' @param ab1 vector of antibiotic interpretations, they will be transformed internally with \code{\link{as.rsi}}
|
||||
#' @param ab2 like \code{ab}, a vector of antibiotic interpretations. Use this to calculate (the lack of) co-resistance: the probability where one of two drugs have a susceptible result. See Examples.
|
||||
#' @param include_I logical to indicate whether antimicrobial interpretations of "I" should be included
|
||||
#' @param minimum minimal amount of available isolates. Any number lower than \code{minimum} will return \code{NA}. The default number of \code{30} isolates is advised by the CLSI as best practice, see Source.
|
||||
#' @param as_percent logical to indicate whether the output must be returned as percent (text), will else be a double
|
||||
#' @param interpretation antimicrobial interpretation
|
||||
#' @param info \emph{DEPRECATED} calculate the amount of available isolates and print it, like \code{n = 423}
|
||||
#' @param warning \emph{DEPRECATED} show a warning when the available amount of isolates is below \code{minimum}
|
||||
#' @details \strong{Remember that you should filter your table to let it contain only first isolates!} Use \code{\link{first_isolate}} to determine them in your data set.
|
||||
#'
|
||||
#' The functions \code{resistance} and \code{susceptibility} are wrappers around \code{IR} and \code{S}, respectively. All functions except \code{rsi} use hybrid evaluation (i.e. using C++), which makes these functions 20-30 times faster than the old \code{rsi} function. This latter function is still available for backwards compatibility but is deprecated.
|
||||
#' The functions \code{resistance} and \code{susceptibility} are wrappers around \code{rsi_IR} and \code{rsi_S}, respectively. All functions use hybrid evaluation (i.e. using C++), which makes these functions 20-30 times faster than the old \code{\link{rsi}} function. This latter function is still available for backwards compatibility but is deprecated.
|
||||
#' \if{html}{
|
||||
#' \cr\cr
|
||||
#' To calculate the probability (\emph{p}) of susceptibility of one antibiotic, we use this formula:
|
||||
@ -47,48 +44,57 @@
|
||||
#' @source \strong{M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition}, 2014, \emph{Clinical and Laboratory Standards Institute (CLSI)}. \url{https://clsi.org/standards/products/microbiology/documents/m39/}.
|
||||
#' @keywords resistance susceptibility rsi_df rsi antibiotics isolate isolates
|
||||
#' @return Double or, when \code{as_percent = TRUE}, a character.
|
||||
#' @rdname resistance
|
||||
#' @rdname rsi_IR
|
||||
#' @name rsi_IR
|
||||
#' @export
|
||||
#' @examples
|
||||
#' # Calculate resistance
|
||||
#' R(septic_patients$amox)
|
||||
#' IR(septic_patients$amox)
|
||||
#' rsi_R(septic_patients$amox)
|
||||
#' rsi_IR(septic_patients$amox)
|
||||
#'
|
||||
#' # Or susceptibility
|
||||
#' S(septic_patients$amox)
|
||||
#' SI(septic_patients$amox)
|
||||
#' rsi_S(septic_patients$amox)
|
||||
#' rsi_SI(septic_patients$amox)
|
||||
#'
|
||||
#' # Since n_rsi counts available isolates (and is used as denominator),
|
||||
#' # you can calculate back to e.g. count resistant isolates:
|
||||
#' IR(septic_patients$amox) * n_rsi(septic_patients$amox)
|
||||
#' rsi_IR(septic_patients$amox) * n_rsi(septic_patients$amox)
|
||||
#'
|
||||
#' library(dplyr)
|
||||
#' septic_patients %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(p = S(cipr),
|
||||
#' n = n_rsi(cipr)) # n_rsi works like n_distinct in dplyr
|
||||
#'
|
||||
#' # Calculate co-resistance between amoxicillin/clav acid and gentamicin,
|
||||
#' # so we can see that combination therapy does a lot more than mono therapy:
|
||||
#' S(septic_patients$amcl) # p = 67.3%
|
||||
#' n_rsi(septic_patients$amcl) # n = 1570
|
||||
#'
|
||||
#' S(septic_patients$gent) # p = 74.0%
|
||||
#' n_rsi(septic_patients$gent) # n = 1842
|
||||
#'
|
||||
#' with(septic_patients,
|
||||
#' S(amcl, gent)) # p = 92.1%
|
||||
#' with(septic_patients,
|
||||
#' n_rsi(amcl, gent)) # n = 1504
|
||||
#' summarise(p = rsi_S(cipr),
|
||||
#' n = rsi_n(cipr)) # n_rsi works like n_distinct in dplyr
|
||||
#'
|
||||
#' septic_patients %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(cipro_p = S(cipr, as_percent = TRUE),
|
||||
#' cipro_n = n_rsi(cipr),
|
||||
#' genta_p = S(gent, as_percent = TRUE),
|
||||
#' genta_n = n_rsi(gent),
|
||||
#' combination_p = S(cipr, gent, as_percent = TRUE),
|
||||
#' combination_n = n_rsi(cipr, gent))
|
||||
#' summarise(R = rsi_R(cipr, as_percent = TRUE),
|
||||
#' I = rsi_I(cipr, as_percent = TRUE),
|
||||
#' S = rsi_S(cipr, as_percent = TRUE),
|
||||
#' n = rsi_n(cipr), # also: n_rsi, works like n_distinct in dplyr
|
||||
#' total = n()) # this is the length, NOT the amount of tested isolates
|
||||
#'
|
||||
#' # Calculate co-resistance between amoxicillin/clav acid and gentamicin,
|
||||
#' # so we can see that combination therapy does a lot more than mono therapy:
|
||||
#' rsi_S(septic_patients$amcl) # S = 67.3%
|
||||
#' rsi_n(septic_patients$amcl) # n = 1570
|
||||
#'
|
||||
#' rsi_S(septic_patients$gent) # S = 74.0%
|
||||
#' rsi_n(septic_patients$gent) # n = 1842
|
||||
#'
|
||||
#' with(septic_patients,
|
||||
#' rsi_S(amcl, gent)) # S = 92.1%
|
||||
#' with(septic_patients, # n = 1504
|
||||
#' rsi_n(amcl, gent))
|
||||
#'
|
||||
#' septic_patients %>%
|
||||
#' group_by(hospital_id) %>%
|
||||
#' summarise(cipro_p = rsi_S(cipr, as_percent = TRUE),
|
||||
#' cipro_n = rsi_n(cipr),
|
||||
#' genta_p = rsi_S(gent, as_percent = TRUE),
|
||||
#' genta_n = rsi_n(gent),
|
||||
#' combination_p = rsi_S(cipr, gent, as_percent = TRUE),
|
||||
#' combination_n = rsi_n(cipr, gent))
|
||||
#'
|
||||
#' \dontrun{
|
||||
#'
|
||||
@ -96,31 +102,45 @@
|
||||
#' my_table %>%
|
||||
#' filter(first_isolate == TRUE,
|
||||
#' genus == "Helicobacter") %>%
|
||||
#' summarise(p = S(amox, metr), # amoxicillin with metronidazole
|
||||
#' n = n_rsi(amox, metr))
|
||||
#' summarise(p = rsi_S(amox, metr), # amoxicillin with metronidazole
|
||||
#' n = rsi_n(amox, metr))
|
||||
#' }
|
||||
#' @rdname resistance
|
||||
#' @name resistance
|
||||
#' @export
|
||||
#' @rdname resistance
|
||||
#' @export
|
||||
S <- function(ab1,
|
||||
ab2 = NULL,
|
||||
minimum = 30,
|
||||
as_percent = FALSE) {
|
||||
susceptibility(ab1 = ab1,
|
||||
ab2 = ab2,
|
||||
include_I = FALSE,
|
||||
minimum = minimum,
|
||||
as_percent = as_percent)
|
||||
rsi_R <- function(ab1,
|
||||
minimum = 30,
|
||||
as_percent = FALSE) {
|
||||
resistance(ab1 = ab1,
|
||||
include_I = FALSE,
|
||||
minimum = minimum,
|
||||
as_percent = as_percent)
|
||||
}
|
||||
|
||||
#' @rdname resistance
|
||||
#' @rdname rsi_IR
|
||||
#' @export
|
||||
SI <- function(ab1,
|
||||
ab2 = NULL,
|
||||
minimum = 30,
|
||||
as_percent = FALSE) {
|
||||
rsi_IR <- function(ab1,
|
||||
minimum = 30,
|
||||
as_percent = FALSE) {
|
||||
resistance(ab1 = ab1,
|
||||
include_I = TRUE,
|
||||
minimum = minimum,
|
||||
as_percent = as_percent)
|
||||
}
|
||||
|
||||
#' @rdname rsi_IR
|
||||
#' @export
|
||||
rsi_I <- function(ab1,
|
||||
minimum = 30,
|
||||
as_percent = FALSE) {
|
||||
intermediate(ab1 = ab1,
|
||||
minimum = minimum,
|
||||
as_percent = as_percent)
|
||||
}
|
||||
|
||||
#' @rdname rsi_IR
|
||||
#' @export
|
||||
rsi_SI <- function(ab1,
|
||||
ab2 = NULL,
|
||||
minimum = 30,
|
||||
as_percent = FALSE) {
|
||||
susceptibility(ab1 = ab1,
|
||||
ab2 = ab2,
|
||||
include_I = TRUE,
|
||||
@ -128,51 +148,20 @@ SI <- function(ab1,
|
||||
as_percent = as_percent)
|
||||
}
|
||||
|
||||
#' @rdname resistance
|
||||
#' @rdname rsi_IR
|
||||
#' @export
|
||||
IR <- function(ab1,
|
||||
minimum = 30,
|
||||
as_percent = FALSE) {
|
||||
resistance(ab1 = ab1,
|
||||
include_I = TRUE,
|
||||
minimum = minimum,
|
||||
as_percent = as_percent)
|
||||
rsi_S <- function(ab1,
|
||||
ab2 = NULL,
|
||||
minimum = 30,
|
||||
as_percent = FALSE) {
|
||||
susceptibility(ab1 = ab1,
|
||||
ab2 = ab2,
|
||||
include_I = FALSE,
|
||||
minimum = minimum,
|
||||
as_percent = as_percent)
|
||||
}
|
||||
|
||||
#' @rdname resistance
|
||||
#' @export
|
||||
R <- function(ab1,
|
||||
minimum = 30,
|
||||
as_percent = FALSE) {
|
||||
resistance(ab1 = ab1,
|
||||
include_I = FALSE,
|
||||
minimum = minimum,
|
||||
as_percent = as_percent)
|
||||
}
|
||||
|
||||
#' @rdname resistance
|
||||
#' @export
|
||||
n_rsi <- function(ab1, ab2 = NULL) {
|
||||
if (NCOL(ab1) > 1) {
|
||||
stop('`ab` must be a vector of antimicrobial interpretations', call. = FALSE)
|
||||
}
|
||||
if (!is.rsi(ab1)) {
|
||||
ab1 <- as.rsi(ab1)
|
||||
}
|
||||
if (!is.null(ab2)) {
|
||||
if (NCOL(ab2) > 1) {
|
||||
stop('`ab2` must be a vector of antimicrobial interpretations', call. = FALSE)
|
||||
}
|
||||
if (!is.rsi(ab2)) {
|
||||
ab2 <- as.rsi(ab2)
|
||||
}
|
||||
sum(!is.na(ab1) & !is.na(ab2))
|
||||
} else {
|
||||
sum(!is.na(ab1))
|
||||
}
|
||||
}
|
||||
|
||||
#' @rdname resistance
|
||||
#' @rdname rsi_IR
|
||||
#' @export
|
||||
resistance <- function(ab1,
|
||||
include_I = TRUE,
|
||||
@ -214,7 +203,45 @@ resistance <- function(ab1,
|
||||
}
|
||||
}
|
||||
|
||||
#' @rdname resistance
|
||||
#' @rdname rsi_IR
|
||||
#' @export
|
||||
intermediate <- function(ab1,
|
||||
minimum = 30,
|
||||
as_percent = FALSE) {
|
||||
|
||||
if (NCOL(ab1) > 1) {
|
||||
stop('`ab1` must be a vector of antimicrobial interpretations', call. = FALSE)
|
||||
}
|
||||
if (!is.numeric(minimum)) {
|
||||
stop('`minimum` must be numeric', call. = FALSE)
|
||||
}
|
||||
if (!is.logical(as_percent)) {
|
||||
stop('`as_percent` must be logical', call. = FALSE)
|
||||
}
|
||||
|
||||
# ab_name <- deparse(substitute(ab))
|
||||
|
||||
if (!is.rsi(ab1)) {
|
||||
x <- as.rsi(ab1)
|
||||
warning("Increase speed by transforming to class `rsi` on beforehand: df %>% mutate_at(vars(col10:col20), as.rsi)")
|
||||
} else {
|
||||
x <- ab1
|
||||
}
|
||||
total <- length(x) - sum(is.na(x)) # faster than C++
|
||||
if (total < minimum) {
|
||||
# warning("Too few isolates available for ", ab_name, ": ", total, " < ", minimum, "; returning NA.", call. = FALSE)
|
||||
return(NA)
|
||||
}
|
||||
found <- .Call(`_AMR_rsi_calc_I`, x)
|
||||
|
||||
if (as_percent == TRUE) {
|
||||
percent(found / total, force_zero = TRUE)
|
||||
} else {
|
||||
found / total
|
||||
}
|
||||
}
|
||||
|
||||
#' @rdname rsi_IR
|
||||
#' @export
|
||||
susceptibility <- function(ab1,
|
||||
ab2 = NULL,
|
||||
@ -275,7 +302,37 @@ susceptibility <- function(ab1,
|
||||
}
|
||||
}
|
||||
|
||||
#' @rdname resistance
|
||||
#' @rdname rsi_IR
|
||||
#' @export
|
||||
rsi_n <- function(ab1, ab2 = NULL) {
|
||||
if (NCOL(ab1) > 1) {
|
||||
stop('`ab` must be a vector of antimicrobial interpretations', call. = FALSE)
|
||||
}
|
||||
if (!is.rsi(ab1)) {
|
||||
ab1 <- as.rsi(ab1)
|
||||
}
|
||||
if (!is.null(ab2)) {
|
||||
if (NCOL(ab2) > 1) {
|
||||
stop('`ab2` must be a vector of antimicrobial interpretations', call. = FALSE)
|
||||
}
|
||||
if (!is.rsi(ab2)) {
|
||||
ab2 <- as.rsi(ab2)
|
||||
}
|
||||
sum(!is.na(ab1) & !is.na(ab2))
|
||||
} else {
|
||||
sum(!is.na(ab1))
|
||||
}
|
||||
}
|
||||
|
||||
#' @rdname rsi_IR
|
||||
#' @export
|
||||
n_rsi <- rsi_n
|
||||
|
||||
#' @inherit resistance
|
||||
#' @description This function is deprecated. Use \code{\link{rsi_IR}} instead.
|
||||
#' @param info calculate the amount of available isolates and print it, like \code{n = 423}
|
||||
#' @param warning show a warning when the available amount of isolates is below \code{minimum}
|
||||
#' @param interpretation antimicrobial interpretation
|
||||
#' @export
|
||||
rsi <- function(ab1,
|
||||
ab2 = NA,
|
||||
Reference in New Issue
Block a user