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(v1.2.0.9019) ab_from_text() dose and administration
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184
R/ab_from_text.R
184
R/ab_from_text.R
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# Visit our website for more info: https://msberends.gitlab.io/AMR. #
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# ==================================================================== #
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#' Retrieve antimicrobial drugs from clinical text
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#' Retrieve antimicrobial drug names and doses from clinical text
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#'
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#' Use this function on e.g. clinical texts from health care records. It returns a [list] with all antimicrobial drugs found in the texts.
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#' Use this function on e.g. clinical texts from health care records. It returns a [list] with all antimicrobial drugs, doses and forms of administration found in the texts.
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#' @inheritSection lifecycle Maturing lifecycle
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#' @param text text to analyse
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#' @param collapse character to pass on to `paste(..., collapse = ...)` to only return one character per element of `text`, see Examples
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#' @param translate_ab a column name of the [antibiotics] data set to translate the antibiotic abbreviations to, using [ab_property()]. Defaults to `FALSE`. Using `TRUE` is equal to using "name".
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#' @param type type of property to search for, either `"drug"`, `"dose"` or `"administration"`, see *Examples*
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#' @param collapse character to pass on to `paste(..., collapse = ...)` to only return one character per element of `text`, see *Examples*
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#' @param translate_ab if `type = "drug"`: a column name of the [antibiotics] data set to translate the antibiotic abbreviations to, using [ab_property()]. Defaults to `FALSE`. Using `TRUE` is equal to using "name".
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#' @param ... parameters passed on to [as.ab()]
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#' @details Without using `collapse`, this function will return a [list]. This can be convenient to use e.g. inside a `mutate()`):\cr
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#' @details This function is also internally used by [as.ab()], although it then only searches for the first drug name and will throw a note if more drug names could have been returned.
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#'
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#' ## Parameter `type`
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#' At default, the function will search for antimicrobial drug names. All text elements will be searched for official names, ATC codes and brand names. As it uses [as.ab()] internally, it will correct for misspelling.
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#'
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#' With `type = "dose"` (or similar, like "dosing", "doses"), all text elements will be searched for numeric values that are higher than 100 and do not resemble years. The output will be numeric. It supports any unit (g, mg, IE, etc.) and multiple values in one clinical text, see *Examples*.
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#'
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#' With `type = "administration"` (or abbreviations, like "admin", "adm"), all text elements will be searched for a form of drug administration. It supports the following forms (including common abbreviations): buccal, implant, inhalation, instillation, intravenous, nasal, oral, parenteral, rectal, sublingual, transdermal and vaginal. Abbreviations for oral (such as 'po', 'per os') will become "oral", all values for intravenous (such as 'iv', 'intraven') will become "iv". It supports multiple values in one clinical text, see *Examples*.
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#'
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#' ## Parameter `collapse`
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#' Without using `collapse`, this function will return a [list]. This can be convenient to use e.g. inside a `mutate()`):\cr
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#' `df %>% mutate(abx = ab_from_text(clinical_text))`
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#'
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#' The returned AB codes can be transformed to official names, groups, etc. with all [ab_property()] functions like [ab_name()] and [ab_group()], or by using the `translate_ab` parameter.
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#'
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#' With using `collapse`, this function will return a [character]:\cr
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#' `df %>% mutate(abx = ab_from_text(clinical_text, collapse = "|"))`
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#'
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#' This function is also internally used by [as.ab()], although it then only returns the first hit and will throw a note if more results could have been returned.
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#' @export
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#' @return A [list], or a [character] if `collapse` is not `NULL`
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#' @inheritSection AMR Read more on our website!
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#' @examples
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#' # mind the bad spelling of amoxicillin in this line,
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#' # straight from a true health care record:
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#' ab_from_text("28/03/2020 regular amoxicilliin 500mg po tds")
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#'
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#' ab_from_text("administered amoxi/clav and cipro")
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#' ab_from_text("administered amoxi/clav and cipro", collapse = ", ")
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#' ab_from_text("500 mg amoxi po and 400mg cipro iv")
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#' ab_from_text("500 mg amoxi po and 400mg cipro iv", type = "dose")
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#' ab_from_text("500 mg amoxi po and 400mg cipro iv", type = "admin")
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#'
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#' # if you want to know which antibiotic groups were administered, check it:
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#' abx <- ab_from_text("administered amoxi/clav and cipro")
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#' ab_from_text("500 mg amoxi po and 400mg cipro iv", collapse = ", ")
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#'
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#' # if you want to know which antibiotic groups were administered, do e.g.:
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#' abx <- ab_from_text("500 mg amoxi po and 400mg cipro iv")
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#' ab_group(abx[[1]])
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#'
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#' if (require(dplyr)) {
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#' tibble(clinical_text = c("given cipro and mero",
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#' "started on doxy today")) %>%
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#' mutate(abx = ab_from_text(clinical_text),
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#' abx2 = ab_from_text(clinical_text,
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#' collapse = "|"),
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#' abx3 = ab_from_text(clinical_text,
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#' collapse = "|",
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#' translate_ab = "name"))
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#' tibble(clinical_text = c("given 400mg cipro and 500 mg amox",
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#' "started on doxy iv today")) %>%
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#' mutate(abx_codes = ab_from_text(clinical_text),
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#' abx_doses = ab_from_text(clinical_text, type = "doses"),
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#' abx_admin = ab_from_text(clinical_text, type = "admin"),
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#' abx_coll = ab_from_text(clinical_text, collapse = "|"),
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#' abx_coll_names = ab_from_text(clinical_text,
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#' collapse = "|",
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#' translate_ab = "name"),
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#' abx_coll_doses = ab_from_text(clinical_text,
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#' type = "doses",
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#' collapse = "|"),
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#' abx_coll_admin = ab_from_text(clinical_text,
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#' type = "admin",
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#' collapse = "|"))
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#'
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#' }
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ab_from_text <- function(text, collapse = NULL, translate_ab = FALSE, ...) {
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ab_from_text <- function(text,
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type = c("drug", "dose", "administration"),
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collapse = NULL,
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translate_ab = FALSE,
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...) {
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if (missing(type)) {
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type <- type[1L]
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}
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type <- tolower(trimws(type))
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stop_if(length(type) != 1, "`type` must be of length 1")
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text <- tolower(as.character(text))
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translate_ab <- get_translate_ab(translate_ab)
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abbr <- unlist(antibiotics$abbreviations)
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abbr <- abbr[nchar(abbr) >= 4]
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names <- substr(antibiotics$name, 1, 5)
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synonyms <- unlist(antibiotics$synonyms)
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synonyms <- synonyms[nchar(synonyms) >= 4]
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to_regex <- function(x) {
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paste0("^(",
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paste0(unique(gsub("[^a-z0-9]", ".*", sort(tolower(x)))), collapse = "|"),
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").*")
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}
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text_split_all <- strsplit(text, "[ ;.,:/\\|-]")
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result <- lapply(text_split_all, function(text_split) {
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suppressWarnings(
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out <- as.ab(unique(c(text_split[grep(to_regex(abbr), text_split)],
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text_split[grep(to_regex(names), text_split)],
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# regular expression must not be too long, so split synonyms in two:
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text_split[grep(to_regex(synonyms[c(1:0.5 * length(synonyms))]), text_split)],
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text_split[grep(to_regex(synonyms[c(0.5 * length(synonyms):length(synonyms))]), text_split)])),
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...))
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out <- out[!is.na(out)]
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if (length(out) == 0) {
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as.ab(NA)
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} else {
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if (!isFALSE(translate_ab)) {
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out <- ab_property(out, property = translate_ab, initial = FALSE)
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}
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out
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if (type %like% "(drug|ab|anti)") {
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translate_ab <- get_translate_ab(translate_ab)
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abbr <- unlist(antibiotics$abbreviations)
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abbr <- abbr[nchar(abbr) >= 4]
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names_atc <- substr(c(antibiotics$name, antibiotics$atc), 1, 5)
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synonyms <- unlist(antibiotics$synonyms)
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synonyms <- synonyms[nchar(synonyms) >= 4]
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to_regex <- function(x) {
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paste0("^(",
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paste0(unique(gsub("[^a-z0-9]", ".*", sort(tolower(x)))), collapse = "|"),
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").*")
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}
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})
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if (!is.null(collapse)) {
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result <- sapply(result, function(x) paste0(x, collapse = collapse))
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result <- lapply(text_split_all, function(text_split) {
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suppressWarnings(
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out <- as.ab(unique(c(text_split[grep(to_regex(abbr), text_split)],
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text_split[grep(to_regex(names_atc), text_split)],
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# regular expression must not be too long, so split synonyms in two:
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text_split[grep(to_regex(synonyms[c(1:0.5 * length(synonyms))]), text_split)],
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text_split[grep(to_regex(synonyms[c(0.5 * length(synonyms):length(synonyms))]), text_split)])),
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...))
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out <- out[!is.na(out)]
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if (length(out) == 0) {
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as.ab(NA)
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} else {
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if (!isFALSE(translate_ab)) {
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out <- ab_property(out, property = translate_ab, initial = FALSE)
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}
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out
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}
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})
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} else if (type %like% "dos") {
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text_split_all <- strsplit(text, " ")
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result <- lapply(text_split_all, function(text_split) {
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text_split <- text_split[text_split %like% "^[0-9]{2,}(/[0-9]+)?[a-z]*$"]
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# only left part of "/", like 500 in "500/125"
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text_split <- gsub("/.*", "", text_split)
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text_split <- gsub(",", ".", text_split, fixed = TRUE) # foreign system using comma as decimal sep
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text_split <- as.double(gsub("[^0-9.]", "", text_split))
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# minimal 100 units/mg and no years that unlikely doses
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text_split <- text_split[text_split >= 100 & !text_split %in% c(1951:1999, 2001:2049)]
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if (length(text_split) > 0) {
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text_split
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} else {
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NA_real_
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}
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})
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} else if (type %like% "adm") {
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result <- lapply(text_split_all, function(text_split) {
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text_split <- text_split[text_split %like% "(^iv$|intraven|^po$|per os|oral|implant|inhal|instill|nasal|paren|rectal|sublingual|buccal|trans.*dermal|vaginal)"]
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if (length(text_split) > 0) {
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text_split <- gsub("(^po$|.*per os.*)", "oral", text_split)
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text_split <- gsub("(^iv$|.*intraven.*)", "iv", text_split)
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text_split
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} else {
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NA_character_
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}
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})
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} else {
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stop_("`type` must be either 'drug', 'dose' or 'administration'")
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}
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# collapse text if needed
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if (!is.null(collapse)) {
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result <- sapply(result, function(x) {
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if(length(x) == 1 & all(is.na(x))) {
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NA_character_
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} else {
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paste0(x, collapse = collapse)
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}
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})
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}
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result
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}
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