HEART_scores {RiskScorescvd}

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

Usage

HEART_scores(
  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
)

Arguments

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

typical_symptoms.num

a numeric vector of the number of typical symptoms

ecg.normal

a binary numeric vector, 1 = yes and 0 = no

abn.repolarisation

a binary numeric vector, 1 = yes and 0 = no

ecg.st.depression

a binary numeric vector, 1 = yes and 0 = no

Age

a numeric vector of age values, in years

diabetes

a binary numeric vector, 1 = yes and 0 = no

smoker

a binary numeric vector, 1 = yes and 0 = no

hypertension

a binary numeric vector, 1 = yes and 0 = no

hyperlipidaemia

a binary numeric vector, 1 = yes and 0 = no

family.history

a binary numeric vector, 1 = yes and 0 = no

atherosclerotic.disease

a binary numeric vector, 1 = yes and 0 = no

presentation_hstni

a continuous numeric vector of the troponin levels

Gender

a binary character vector of sex values. Categories should include only 'male' or 'female'

classify

a logical parameter to indicate classification of Scores "TRUE" or none "FALSE"

Value

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)