mirror of
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177 lines
6.6 KiB
R
177 lines
6.6 KiB
R
# ==================================================================== #
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# TITLE #
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# AMR: An R Package for Working with Antimicrobial Resistance Data #
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# #
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# SOURCE #
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# https://github.com/msberends/AMR #
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# #
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# CITE AS #
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# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
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# (2022). AMR: An R Package for Working with Antimicrobial Resistance #
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# Data. Journal of Statistical Software, 104(3), 1-31. #
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# doi:10.18637/jss.v104.i03 #
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# #
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# Developed at the University of Groningen, the Netherlands, in #
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# collaboration with non-profit organisations Certe Medical #
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# Diagnostics & Advice, and University Medical Center Groningen. #
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# #
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# This R package is free software; you can freely use and distribute #
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# it for both personal and commercial purposes under the terms of the #
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# GNU General Public License version 2.0 (GNU GPL-2), as published by #
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# the Free Software Foundation. #
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# We created this package for both routine data analysis and academic #
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# research and it was publicly released in the hope that it will be #
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# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
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# #
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# Visit our website for the full manual and a complete tutorial about #
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# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
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# ==================================================================== #
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library(dplyr)
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library(readxl)
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library(cleaner)
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# URL:
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# https://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/Dosages_v_11.0_Breakpoint_Tables.pdf
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# download the PDF file, open in Acrobat Pro and export as Excel workbook
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breakpoints_version <- 11
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dosage_source <- read_excel("data-raw/Dosages_v_11.0_Breakpoint_Tables.xlsx", skip = 5, na = "None") %>%
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format_names(snake_case = TRUE, penicillins = "drug") %>%
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filter(!tolower(standard_dosage) %in% c("standard dosage_source", "under review")) %>%
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filter(!is.na(standard_dosage)) %>%
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# keep only one drug in the table
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arrange(desc(drug)) %>%
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mutate(drug = gsub("(.*) ([(]|iv|oral).*", "\\1", drug)) %>%
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# distinct(drug, .keep_all = TRUE) %>%
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arrange(drug) %>%
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mutate(
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ab = as.ab(drug),
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ab_name = ab_name(ab, language = NULL)
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)
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dosage_source <- bind_rows(
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# oral
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dosage_source %>%
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filter(standard_dosage %like% " oral") %>%
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mutate(
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standard_dosage = gsub("oral.*", "oral", standard_dosage),
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high_dosage = if_else(high_dosage %like% "oral",
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gsub("oral.*", "oral", high_dosage),
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NA_character_
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)
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),
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# iv
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dosage_source %>%
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filter(standard_dosage %like% " iv") %>%
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mutate(
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standard_dosage = gsub(".* or ", "", standard_dosage),
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high_dosage = if_else(high_dosage %like% "( or | iv)",
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gsub(".* or ", "", high_dosage),
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NA_character_
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)
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),
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# im
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dosage_source %>%
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filter(standard_dosage %like% " im")
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) %>%
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arrange(drug)
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get_dosage_lst <- function(col_data) {
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standard <- col_data %>%
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# remove new lines
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gsub(" ?(\n|\t)+ ?", " ", .) %>%
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# keep only the first suggestion, replace all after 'or' and more informative texts
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gsub("(.*?) (or|with|loading|depending|over|by) .*", "\\1", .) %>%
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# remove (1 MU)
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gsub(" [(][0-9] [A-Z]+[)]", "", .) %>%
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# remove parentheses
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gsub("[)(]", "", .) %>%
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# remove drug names
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gsub(" [a-z]{5,99}( |$)", " ", .) %>%
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gsub(" [a-z]{5,99}( |$)", " ", .) %>%
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gsub(" (acid|dose)", "", .) # %>%
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# keep lowest value only (25-30 mg -> 25 mg)
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# gsub("[-].*? ", " ", .)
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dosage_lst <- lapply(
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strsplit(standard, " x "),
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function(x) {
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dose <- x[1]
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if (dose %like% "under") {
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dose <- NA_character_
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}
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admin <- x[2]
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list(
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dose = trimws(dose),
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dose_times = gsub("^([0-9.]+).*", "\\1", admin),
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administration = clean_character(admin),
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notes = "",
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original_txt = ""
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)
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}
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)
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for (i in seq_len(length(col_data))) {
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dosage_lst[[i]]$original_txt <- gsub("\n", " ", col_data[i])
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if (col_data[i] %like% " (or|with|loading|depending|over) ") {
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dosage_lst[[i]]$notes <- gsub("\n", " ", gsub(".* ((or|with|loading|depending|over) .*)", "\\1", col_data[i]))
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}
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}
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dosage_lst
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}
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standard <- get_dosage_lst(dosage_source$standard_dosage)
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high <- get_dosage_lst(dosage_source$high_dosage)
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uti <- get_dosage_lst(dosage_source$uncomplicated_uti)
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dosage <- bind_rows(
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# standard dose
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data.frame(
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ab = dosage_source$ab,
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name = dosage_source$ab_name,
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type = "standard_dosage",
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dose = sapply(standard, function(x) x$dose),
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dose_times = sapply(standard, function(x) x$dose_times),
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administration = sapply(standard, function(x) x$administration),
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notes = sapply(standard, function(x) x$notes),
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original_txt = sapply(standard, function(x) x$original_txt),
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stringsAsFactors = FALSE
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),
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# high dose
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data.frame(
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ab = dosage_source$ab,
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name = dosage_source$ab_name,
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type = "high_dosage",
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dose = sapply(high, function(x) x$dose),
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dose_times = sapply(high, function(x) x$dose_times),
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administration = sapply(high, function(x) x$administration),
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notes = sapply(high, function(x) x$notes),
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original_txt = sapply(high, function(x) x$original_txt),
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stringsAsFactors = FALSE
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),
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# UTIs
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data.frame(
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ab = dosage_source$ab,
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name = dosage_source$ab_name,
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type = "uncomplicated_uti",
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dose = sapply(uti, function(x) x$dose),
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dose_times = sapply(uti, function(x) x$dose_times),
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administration = sapply(uti, function(x) x$administration),
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notes = sapply(uti, function(x) x$notes),
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original_txt = sapply(uti, function(x) x$original_txt),
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stringsAsFactors = FALSE
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)
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) %>%
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mutate(
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eucast_version = breakpoints_version,
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dose_times = as.integer(dose_times),
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administration = gsub("([a-z]+) .*", "\\1", administration)
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) %>%
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arrange(name, administration, type) %>%
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filter(!is.na(dose), dose != ".") %>%
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as.data.frame(stringsAsFactors = FALSE)
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rownames(dosage) <- NULL
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usethis::use_data(dosage, internal = FALSE, overwrite = TRUE, version = 2)
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