HEART {RiskScorescvd}

History, ECG, Age, Risk factors and Troponin (HEART) risk score

Description

This function implements the HEART score calculation as a vector

History - Absence of history for coronary ischemia: nonspecific = 0 Nonspecific + suspicious elements: moderately suspicious = 1 Mainly suspicious elements (middle- or left-sided, / heavy chest pain, radiation, / and/or relief of symptoms by sublingual nitrates): = 2

EGG - Normal ECG according to Minnesota criteria (what's this criteria?) = 0 Repolarization abnormalities without / significant ST-segment depression or elevation = 1 Presence of a bundle branch block or pacemaker rhythm, / typical abnormalities indicative of left ventricular hypertrophy, / repolarization abnormalities probably caused by digoxin use, / or in case of unchanged known repolarization disturbances. = 1 Significant ST-segment depressions / or elevations in absence of a bundle branch block, / left ventricular hypertrophy, or the use of digoxin = 2

Age - Younger than 45 = 0 45 to 65 years old = 1 65 years or older = 2

Risk facrtor - Currently treated diabetes mellitus, / current or recent (<90 days) smoker, / diagnosed and/or treated hypertension, / diagnosed hypercholesterolemia, / family history of coronary artery disease, obesity (body mass index BMI >30), or a history of significant atherosclerosis, / (coronary revascularization, myocardial infarction, stroke, / or peripheral arterial disease, / irrespective of the risk factors for coronary artery disease) None of the above = 0 One or two of the above = 1 Three or more of the above = 2

Troponin T or I - Below the threshold for positivity = 0 A Between 1 and 3 times the threshold for positivity = 1 A higher than 3 times the threshold for positivity = 2 A

Two possible outcomes: 0-3 = Low risk 4-6 = Moderate risk Over 7 = High risk

The HEART score: A guide to its application in the emergency department paper reference Website: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6005932/

Usage

HEART(
  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 = classify
)

Arguments

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 vector with HEART score calculations and/or a vector of their classifications if indicated

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

 results <- cohort_xx %>% 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 = FALSE))