R/04_EDACS_df.R

In RiskScorescvd: Cardiovascular Risk Scores Calculator

#' EDACS score function for data frame;
#' EDACS = Emergency Department Assessment of Chest Pain Score
#'
#' @description
#' This function allows you to calculate the EDACS score row wise
#' in a data frame with the required variables. It would then retrieve a data
#' frame with two extra columns including the calculations and their classifications
#'
#' @param data
#' A data frame with all the variables needed for calculation:
#' Age, Gender, diabetes, smoker, hypertension, hyperlipidaemia,
#' family.history, sweating, pain.radiation, pleuritic, palpation,
#' ecg.st.depression, ecg.twi,  presentation_hstni, second_hstni, classify
#' @param classify a logical parameter to indicate classification of Scores "TRUE" or none "FALSE"
#' @param ecg.st.depression a binary numeric vector, 1 = yes and 0 = no
#' @param Age a numeric vector of age values, in years
#' @param diabetes a binary numeric vector, 1 = yes and 0 = no
#' @param smoker a binary numeric vector, 1 = yes and 0 = no
#' @param hypertension a binary numeric vector, 1 = yes and 0 = no
#' @param hyperlipidaemia a binary numeric vector, 1 = yes and 0 = no
#' @param family.history a binary numeric vector, 1 = yes and 0 = no
#' @param presentation_hstni a continuous numeric vector of the troponin levels
#' @param Gender a binary character vector of sex values. Categories should include only 'male' or 'female'
#' @param sweating a binary numeric vector, 1 = yes and 0 = no
#' @param pain.radiation a binary numeric vector, 1 = yes and 0 = no
#' @param pleuritic a binary numeric vector, 1 = yes and 0 = no
#' @param palpation a binary numeric vector, 1 = yes and 0 = no
#' @param ecg.twi a binary numeric vector, 1 = yes and 0 = no
#' @param second_hstni a binary numeric vector, 1 = yes and 0 = no
#'
#' @keywords
#' EDACS Age Gender diabetes smoker hypertension hyperlipidaemia
#' family.history sweating pain.radiation pleuritic palpation
#' ecg.st.depression ecg.twi  presentation_hstni second_hstni classify
#'
#' @return
#' data frame with two extra columns including the 'EDACS_score' calculations
#' and their classifications, 'EDACS_strat'
#'
#'
#' @examples
#'
#' # Create a data frame or list with the necessary variables
#' # Set the number of rows
#' num_rows <- 100
#'
#' # Create a larger dataset with 100 rows
#' cohort_xx <- data.frame(
#'   typical_symptoms.num = as.numeric(sample(0:6, num_rows, replace = TRUE)),
#'   ecg.normal = as.numeric(sample(c(0, 1), num_rows, replace = TRUE)),
#'   abn.repolarisation = as.numeric(sample(c(0, 1), num_rows, replace = TRUE)),
#'   ecg.st.depression = as.numeric(sample(c(0, 1), num_rows, replace = TRUE)),
#'   Age = as.numeric(sample(30:80, num_rows, replace = TRUE)),
#'   diabetes = sample(c(1, 0), num_rows, replace = TRUE),
#'   smoker = sample(c(1, 0), num_rows, replace = TRUE),
#'   hypertension = sample(c(1, 0), num_rows, replace = TRUE),
#'   hyperlipidaemia = sample(c(1, 0), num_rows, replace = TRUE),
#'   family.history = sample(c(1, 0), num_rows, replace = TRUE),
#'   atherosclerotic.disease = sample(c(1, 0), num_rows, replace = TRUE),
#'   presentation_hstni = as.numeric(sample(10:100, num_rows, replace = TRUE)),
#'   Gender = sample(c("male", "female"), num_rows, replace = TRUE),
#'   sweating = as.numeric(sample(c(0, 1), num_rows, replace = TRUE)),
#'   pain.radiation = as.numeric(sample(c(0, 1), num_rows, replace = TRUE)),
#'   pleuritic = as.numeric(sample(c(0, 1), num_rows, replace = TRUE)),
#'   palpation = as.numeric(sample(c(0, 1), num_rows, replace = TRUE)),
#'   ecg.twi = as.numeric(sample(c(0, 1), num_rows, replace = TRUE)),
#'   second_hstni = as.numeric(sample(1:200, num_rows, replace = TRUE))
#' )
#'
#' # Call the function with the cohort_xx
#'
#' result <- EDACS_scores(data = cohort_xx, classify = TRUE)
#' summary(result$EDACS_strat)
#' summary(result$EDACS_score)
#'
#' @importFrom dplyr mutate
#' @importFrom dplyr rename
#' @importFrom dplyr %>%
#' @importFrom dplyr rowwise
#'
#' @export

EDACS_scores <-
  function(data,
           Age = Age,
           Gender = Gender,
           diabetes = diabetes,
           smoker = smoker,
           hypertension = hypertension,
           hyperlipidaemia = hyperlipidaemia,
           family.history = family.history,
           sweating = sweating,
           pain.radiation = pain.radiation,
           pleuritic = pleuritic,
           palpation = palpation,
           ecg.st.depression = ecg.st.depression,
           ecg.twi = ecg.twi,
           presentation_hstni = presentation_hstni,
           second_hstni = second_hstni,
           classify) {
    data <-
      data %>% rename(
        Age = Age,
        Gender = Gender,
        diabetes = diabetes,
        smoker = smoker,
        hypertension = hypertension,
        hyperlipidaemia = hyperlipidaemia,
        family.history = family.history,
        sweating = sweating,
        pain.radiation = pain.radiation,
        pleuritic = pleuritic,
        palpation = palpation,
        ecg.st.depression = ecg.st.depression,
        ecg.twi = ecg.twi,
        presentation_hstni = presentation_hstni,
        second_hstni = second_hstni
      )

    if (classify == TRUE) {
      results <- data  %>% rowwise() %>% mutate(
        EDACS_score = EDACS(
          Age,
          Gender,
          diabetes,
          smoker,
          hypertension,
          hyperlipidaemia,
          family.history,
          sweating,
          pain.radiation,
          pleuritic,
          palpation,
          ecg.st.depression,
          ecg.twi,
          presentation_hstni,
          second_hstni,
          classify = FALSE
        ),
        EDACS_strat = EDACS(
          Age,
          Gender,
          diabetes,
          smoker,
          hypertension,
          hyperlipidaemia,
          family.history,
          sweating,
          pain.radiation,
          pleuritic,
          palpation,
          ecg.st.depression,
          ecg.twi,
          presentation_hstni,
          second_hstni,
          classify = classify
        ) %>% as.factor() %>% ordered(levels = c("Low risk", "Not low risk"))
      )
    }

    else{
      results <- data  %>% rowwise() %>% mutate(
        EDACS_score = EDACS(
          Age,
          Gender,
          diabetes,
          smoker,
          hypertension,
          hyperlipidaemia,
          family.history,
          sweating,
          pain.radiation,
          pleuritic,
          palpation,
          ecg.st.depression,
          ecg.twi,
          presentation_hstni,
          second_hstni,
          classify = classify
        )
      )
    }
    return(results)
  }