GRACE_scores {RiskScorescvd}

GRACE 2.0 score function for data frame; GRACE 2.0 = Global Registry of Acute Coronary Events version 2.0

Description

This function allows you to calculate the GRACE 2.0 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

GRACE_scores(
  data,
  killip.class = killip.class,
  systolic.bp = systolic.bp,
  heart.rate = heart.rate,
  Age = Age,
  creat = creat,
  ecg.st.depression = ecg.st.depression,
  presentation_hstni = presentation_hstni,
  cardiac.arrest = cardiac.arrest,
  Gender = Gender,
  classify
)

Arguments

data

A data frame with all the variables needed for calculation: killip.class, systolic.bp, heart.rate, Age, creat, ecg.st.depression, presentation_hstni, cardiac.arrest, Gender, classify

killip.class

a numeric vector of killip class values, 1 to 4

systolic.bp

a numeric vector of systolic blood pressure continuous values

heart.rate

a numeric vector of heart rate continuous values

Age

a numeric vector of age values, in years

creat

a continuous numeric vector of the creatine levels

ecg.st.depression

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

presentation_hstni

a continuous numeric vector of the troponin levels

cardiac.arrest

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

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

data frame with two extra columns including the 'GRACE_score' calculations and their classifications, 'GRACE_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)),
  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))
)
# Call the function with the cohort_xx
result <- GRACE_scores(data = cohort_xx, classify = TRUE)
summary(result$GRACE_strat)
summary(result$GRACE_score)