# ==================================================================== # # TITLE # # Antimicrobial Resistance (AMR) Analysis # # # # SOURCE # # https://gitlab.com/msberends/AMR # # # # LICENCE # # (c) 2018-2020 Berends MS, Luz CF et al. # # # # 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 more info: https://msberends.gitlab.io/AMR. # # ==================================================================== # library(openxlsx) library(dplyr) library(cleaner) library(AMR) read_EUCAST <- function(sheet, file = "data-raw/v_10.0_Breakpoint_Tables.xlsx") { message("Getting sheet ", sheet) sheet.bak <- sheet raw_data <- read.xlsx(xlsxFile = file, sheet = sheet, colNames = FALSE, skipEmptyRows = FALSE, skipEmptyCols = FALSE, fillMergedCells = TRUE, na.strings = c("", "-", "NA", "IE", "IP")) # in the info header in the Excel file, EUCAST mentions which genera are targeted if (sheet %like% "anaerob.*Gram.*posi") { sheet <- paste0(c("Actinomyces", "Bifidobacterium", "Clostridioides", "Clostridium", "Cutibacterium", "Eggerthella", "Eubacterium", "Lactobacillus", "Propionibacterium", "Staphylococcus saccharolyticus"), collapse = "_") } else if (sheet %like% "anaerob.*Gram.*nega") { sheet <- paste0(c("Bacteroides", "Bilophila", "Fusobacterium", "Mobiluncus", "Parabacteroides", "Porphyromonas", "Prevotella"), collapse = "_") } else if (sheet == "Streptococcus A,B,C,G") { sheet <- paste0(microorganisms %>% filter(genus == "Streptococcus") %>% mutate(lancefield = mo_name(mo, Lancefield = TRUE)) %>% filter(lancefield %like% "^Streptococcus group") %>% pull(fullname), collapse = "_") } else if (sheet %like% "PK.*PD") { sheet <- "UNKNOWN" } mo_sheet <- paste0(as.mo(unlist(strsplit(sheet, "_"))), collapse = "|") set_columns_names <- function(x, cols) { colnames(x) <- cols[1:length(colnames(x))] x } get_mo <- function(x) { for (i in seq_len(length(x))) { y <- trimws(unlist(strsplit(x[i], "(,|and)"))) y <- trimws(gsub("[(].*[)]", "", y)) y <- suppressWarnings(as.mo(y, allow_uncertain = FALSE)) y <- y[!is.na(y) & y != "UNKNOWN"] x[i] <- paste(y, collapse = "|") } x } MICs_with_trailing_superscript <- c(0.0011:0.0019, 11:19, 21:29, 0.51:0.59, 41:49, 81:89, 0.031:0.039, 0.061:0.069, 0.251:0.259, 0.1251:0.1259, 161:169, 321:329) has_zone_diameters <- rep(any(unlist(raw_data) %like% "zone diameter"), nrow(raw_data)) cleaned <- raw_data %>% as_tibble() %>% set_columns_names(LETTERS) %>% transmute(drug = A, MIC_S = B, MIC_R = C, disk_dose = ifelse(has_zone_diameters, E, NA_character_), disk_S = ifelse(has_zone_diameters, `F`, NA_character_), disk_R = ifelse(has_zone_diameters, G, NA_character_)) %>% filter(!is.na(drug), !(is.na(MIC_S) & is.na(MIC_R) & is.na(disk_S) & is.na(disk_R)), !MIC_S %like% "(MIC|S ≤|note)", drug != MIC_S) %>% mutate(administration = case_when(drug %like% "[( ]oral" ~ "oral", drug %like% "[( ]iv" ~ "iv", TRUE ~ NA_character_), uti = ifelse(drug %like% "(UTI|urinary|urine)", TRUE, FALSE), systemic = ifelse(drug %like% "(systemic|septic)", TRUE, FALSE), mo = ifelse(drug %like% "([.]|spp)", get_mo(drug), mo_sheet)) %>% # clean disk doses mutate(disk_dose = clean_character(disk_dose, remove = "[^0-9.-]")) %>% # clean MIC and disk values mutate(MIC_S = gsub(".,.", "", MIC_S), # remove superscript notes with comma, like 0.5^2,3 MIC_R = gsub(".,.", "", MIC_R), disk_S = gsub(".,.", "", disk_S), disk_R = gsub(".,.", "", disk_R), MIC_S = clean_double(MIC_S), # make them valid numeric values MIC_R = clean_double(MIC_R), disk_S = clean_integer(disk_S), disk_R = clean_integer(disk_R), # invalid MIC values have a superscript text, delete those MIC_S = ifelse(MIC_S %in% MICs_with_trailing_superscript, substr(MIC_S, 1, nchar(MIC_S) - 1), MIC_S), MIC_R = ifelse(MIC_R %in% MICs_with_trailing_superscript, substr(MIC_R, 1, nchar(MIC_R) - 1), MIC_R) ) %>% # clean drug names mutate(drug = gsub(" ?[(, ].*$", "", drug), drug = gsub("[1-9]+$", "", drug), ab = as.ab(drug)) %>% select(ab, mo, everything(), -drug) # new row for every different MO mentioned for (i in 1:nrow(cleaned)) { mo <- cleaned[i, "mo", drop = TRUE] if (grepl(pattern = "|", mo, fixed = TRUE)) { mo_vect <- unlist(strsplit(mo, "|", fixed = TRUE)) cleaned[i, "mo"] <- mo_vect[1] for (j in seq_len(length(mo_vect))) { cleaned <- bind_rows(cleaned, cleaned[i ,]) cleaned[nrow(cleaned), "mo"] <- mo_vect[j] } } } cleaned <- cleaned %>% distinct(ab, mo, administration, uti, systemic, .keep_all = TRUE) %>% arrange(ab, mo) %>% mutate_at(c("MIC_S", "MIC_R", "disk_S", "disk_R"), as.double) %>% pivot_longer(c("MIC_S", "MIC_R", "disk_S", "disk_R"), "type") %>% mutate(method = ifelse(type %like% "MIC", "MIC", "DISK"), type = gsub("^.*_", "breakpoint_", type)) %>% pivot_wider(names_from = type, values_from = value) %>% mutate(guideline = "EUCAST 2020", disk_dose = ifelse(method == "DISK", disk_dose, NA_character_), mo = ifelse(mo == "", mo_sheet, mo)) %>% filter(!(is.na(breakpoint_S) & is.na(breakpoint_R))) %>% # comply with rsi_translation for now transmute(guideline, method, site = case_when(uti ~ "UTI", systemic ~ "Systemic", TRUE ~ administration), mo, ab, ref_tbl = sheet.bak, disk_dose = ifelse(!is.na(disk_dose), paste0(disk_dose, "ug"), NA_character_), breakpoint_S, breakpoint_R) cleaned } sheets_to_analyse <- c("Enterobacterales", "Pseudomonas", "S.maltophilia", "Acinetobacter", "Staphylococcus", "Enterococcus", "Streptococcus A,B,C,G", "S.pneumoniae", "Viridans group streptococci", "H.influenzae", "M.catarrhalis", "N.gonorrhoeae", "N.meningitidis", "Anaerobes, Grampositive", "C.difficile", "Anaerobes, Gramnegative", "H.pylori", "L.monocytogenes", "P.multocida", "C.jejuni_C.coli", "Corynebacterium", "A.sanguinicola_A.urinae", "K.kingae", "Aeromonas", "B.pseudomallei", "M.tuberculosis", "PK PD breakpoints") new_EUCAST <- read_EUCAST(sheets_to_analyse[1]) # takes the longest time for (i in 2:length(sheets_to_analyse)) { new_EUCAST <<- new_EUCAST %>% bind_rows(read_EUCAST(sheets_to_analyse[i])) }