AMR/data-raw/read_EUCAST.R

# ==================================================================== #
# TITLE                                                                #
# Antimicrobial Resistance (AMR) Analysis                              #
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# SOURCE                                                               #
# https://gitlab.com/msberends/AMR                                     #
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# (c) 2018-2020 Berends MS, Luz CF et al.                              #
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# This R package is free software; you can freely use and distribute   #
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# GNU General Public License version 2.0 (GNU GPL-2), as published by  #
# the Free Software Foundation.                                        #
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# We created this package for both routine data analysis and academic  #
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library(openxlsx)
library(dplyr)
library(cleaner)
library(AMR)

# USE THIS FUNCTION TO READ THE EUCAST EXCEL FILE THAT CONTAINS THE BREAKPOINT TABLES

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]))
}