SCORE2/OP {RiskScorescvd}

Systematic COronary Risk Evaluation (SCORE) model

Description

This function implements the SCORE2 and SCORE2 older population (OP) score calculation as a vector

formula in SCORE2 Updated Supplementary Material page 9. paper: "SCORE2 risk prediction algorithms: new models to estimate 10-year risk of cardiovascular disease in Europe"

Age 10-year risk of fatal and non-fatal cardiovascular disease

| Low risk | Moderate risk | High risk |
| ————- | ————- | :————-: | ———-:|
| < 50 years | <2.5 | 50 - 69 years | <5 | => 70 years | <7.5

above classifications referred from https://www.inanutshell.ch/en/digital-doctors-bag/score2-and-score2-op/#:~:text=SCORE2

Usage

SCORE2(
  Age = Age,
  Gender = Gender,
  smoker = smoker,
  systolic.bp = systolic.bp,
  diabetes = diabetes,
  total.chol = total.chol,
  total.hdl = total.hdl,
  classify
)

Arguments

Age

a numeric vector of age values, in years

Gender

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

smoker

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

systolic.bp

a numeric vector of systolic blood pressure continuous values

diabetes

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

total.chol

a numeric vector of total cholesterol values, in mmol/L

total.hdl

a numeric vector of total high density lipoprotein total.hdl values, in mmol/L

classify

set TRUE if wish to add a column with the scores' categories

Value

A vector with SCORE2/OP 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),
  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)),
  killip.class = as.numeric(sample(1:4, num_rows, replace = TRUE)),
  systolic.bp = as.numeric(sample(0:300, num_rows, replace = TRUE)),
  heart.rate = as.numeric(sample(0:300, num_rows, replace = TRUE)),
  creat = as.numeric(sample(0:4, num_rows, replace = TRUE)),
  cardiac.arrest = as.numeric(sample(c(0, 1), num_rows, replace = TRUE)),
  previous.pci = as.numeric(sample(c(0, 1), num_rows, replace = TRUE)),
  previous.cabg = as.numeric(sample(c(0, 1), num_rows, replace = TRUE)),
  aspirin = as.numeric(sample(c(0, 1), num_rows, replace = TRUE)),
  number.of.episodes.24h = as.numeric(sample(0:20, num_rows, replace = TRUE)),
  total.chol = as.numeric(sample(5:100, num_rows, replace = TRUE)),
  total.hdl = as.numeric(sample(2:5, num_rows, replace = TRUE)),
  Ethnicity = sample(c("white", "black", "asian", "other"), num_rows, replace = TRUE)
)

# Call the function with the cohort_xx

  results <- cohort_xx %>% rowwise() %>%
  mutate(SCORE2OP_score = SCORE2(Age, Gender, smoker, systolic.bp, diabetes,
  total.chol, total.hdl, classify = FALSE))