R/02_HEART_df.R

In RiskScorescvd: Cardiovascular Risk Scores Calculator

#' HEART risk score function for data frame;
#' HEART = History, ECG, Age, Risk factors, Troponin
#'
#' @description
#' This function allows you to calculate the HEART 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:
#' typical_symptoms.num, ecg.normal, abn.repolarisation, ecg.st.depression,Age,
#' diabetes, smoker, hypertension, hyperlipidaemia, family.history,
#' atherosclerotic.disease, presentation_hstni, Gender
#' @param classify a logical parameter to indicate classification of Scores "TRUE" or none "FALSE"
#' @param  typical_symptoms.num a numeric vector of the number of typical symptoms
#' @param ecg.normal a binary numeric vector,  1 = yes and 0 = no
#' @param abn.repolarisation a binary numeric vector,  1 = yes and 0 = no
#' @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 atherosclerotic.disease 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'
#'
#' @keywords
#' HEART typical_symptoms.num ecg.normal abn.repolarisation ecg.st.depression
#' Age diabetes smoker hypertension hyperlipidaemia family.history
#' atherosclerotic.disease presentation_hstni Gender classify
#'
#' @return
#' a data frame with two extra columns including the HEART score calculations
#' and their classifications
#'
#'
#' @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)
#' )


#' # Call the function with the cohort_xx
#' result <- HEART_scores(data = cohort_xx, classify = TRUE)

#' # Print the results
#' summary(result$HEART_score)
#' summary(result$HEART_strat)
#'
#' @importFrom dplyr mutate
#' @importFrom dplyr rename
#' @importFrom dplyr %>%
#' @importFrom dplyr rowwise
#'
#' @export

HEART_scores <- function(data, typical_symptoms.num = typical_symptoms.num,
                         ecg.normal = ecg.normal,
                         abn.repolarisation = abn.repolarisation,
                         ecg.st.depression = ecg.st.depression,
                         Age = Age,
                         diabetes = diabetes,
                         smoker = smoker,
                         hypertension = hypertension,
                         hyperlipidaemia = hyperlipidaemia,
                         family.history = family.history,
                         atherosclerotic.disease = atherosclerotic.disease,
                         presentation_hstni = presentation_hstni,
                         Gender = Gender, classify) {

  data <- data %>% rename(typical_symptoms.num = typical_symptoms.num,
                          ecg.normal = ecg.normal,
                          abn.repolarisation = abn.repolarisation,
                          ecg.st.depression = ecg.st.depression,
                          Age = Age,
                          diabetes = diabetes,
                          smoker = smoker,
                          hypertension = hypertension,
                          hyperlipidaemia = hyperlipidaemia,
                          family.history = family.history,
                          atherosclerotic.disease = atherosclerotic.disease,
                          presentation_hstni = presentation_hstni,
                          Gender = Gender)

  if (classify == TRUE) {
    results <- data  %>% rowwise() %>% mutate(
      HEART_score = HEART(
        typical_symptoms.num,

        ecg.normal,
        # all 0 = +0

        abn.repolarisation,
        # = paced 1 = +1
        ecg.st.depression,
        #ecg.st.depression = 1 = +2

        Age,
        diabetes,
        smoker,
        hypertension,
        hyperlipidaemia,
        family.history,

        atherosclerotic.disease,

        presentation_hstni,
        Gender ,
        classify = FALSE
      ),
      HEART_strat = HEART(
        typical_symptoms.num,
        ecg.normal,
        abn.repolarisation,
        ecg.st.depression,
        Age,
        diabetes,
        smoker,
        hypertension,
        hyperlipidaemia,
        family.history,
        atherosclerotic.disease,
        presentation_hstni,
        Gender ,
        classify = classify
      ) %>% as.factor() %>% ordered(levels = c(
        "Low risk", "Moderate risk", "High risk"
      ))
    )

  }

  else{
    results <- data  %>% rowwise() %>% mutate(
      HEART_score = HEART(
        typical_symptoms.num,
        ecg.normal,
        abn.repolarisation,
        ecg.st.depression,
        Age,
        diabetes,
        smoker,
        hypertension,
        hyperlipidaemia,
        family.history,
        atherosclerotic.disease,
        presentation_hstni,
        Gender ,
        classify = classify
      )
    )
  }
  return(results)
}