R/AddICU.R

In citronmeliss/predictionpackr: Predictionpackr

#' Add ICU outcome function
#' @param study_data study data as a data frame
#' @export
#'

AddICU <- function(study_data) {

  # Create new columns, ed_admit and icu_admit for combined time and date of arrivial
  study_data <- study_data %>%
    mutate(ed_admit = paste0(doar, toar)) %>%
    mutate(icu_admit = paste0(daicu, taicu))

  # Transform columns into POSIXct object to handle as dates
  study_data$ed_admit <- as.POSIXct(study_data$ed_admit, format = "%Y-%m-%d %H:%M")
  study_data$icu_admit <- as.POSIXct(study_data$icu_admit, format = "%Y-%m-%d %H:%M")

  # Create final columns with time to ICU admission and binary outcome if admitted < 48 h
  study_data <- study_data %>%
    mutate(time_to_icu = difftime(icu_admit, ed_admit, units = "hours")) %>%
    mutate(icu48h = difftime(icu_admit, ed_admit, units = "hours"))

  # Change all who were admitted within 48h to 1, and the rest to 0
  study_data$icu48h <- ifelse(study_data$icu48h <= 48, 1, 0)

  # Convert NA values in icu48h to those of daicu/taicu
  study_data$icu48h <- with(study_data, ifelse(daicu == "0" | taicu == "0", 0, icu48h ))
  study_data$icu48h <- with(study_data, ifelse(daicu == "NA" | taicu == "NA", NA, icu48h))

  # Drop date and time variables, keep doar toar for major surgery function
  study_data <- within(study_data, rm("daicu", "taicu", "ed_admit", "icu_admit", "time_to_icu"))

  return(study_data)

}