EDACS {RiskScorescvd}

Emergency Department Assessment of Chest Pain Score (EDACS) function

Description

This function implements the EDACS score calculation as a vector

Age - 18-45 = 2
46-50 = 4
51-55 = 6
56-60 = 8
61-65 = 10
66-70 = 12
71-75 = 14
76-80 = 16
81-85 = 18
>=86 = 20

Sex -
Female = 0
Male = 6

Known coronary artery disease or >=3 risk factors*
The risk factors only apply to patients 18-50-
no = 0
yes = 4

Symptoms and signs
Diaphoresis no = 0 yes = 3
Pain radiates to arm, shoulder, neck, or jaw no = 0 yes = 5
Pain occurred or worsened with inspiration no = 0 yes = -4
Pain is reproduced by palpation no = 0 yes = -6

Two possible outcomes

Low risk cohort:
EDACS <16 and
EKG shows no new ischemia and
0-hr and 2-hr troponin both negative.
Not low risk cohort:
EDACS >=16 or
EKG shows new ischemia or
0-hr or 2-hr troponin positive.

Usage

EDACS(
  Age = Age,
  Gender = Gender,
  diabetes = diabetes,
  smoker = smoker,
  hypertension = hypertension,
  hyperlipidaemia = hyperlipidaemia,
  family.history = family.history,
  sweating = sweating,
  pain.radiation = pain.radiation,
  pleuritic = pleuritic,
  palpation = palpation,
  ecg.st.depression = ecg.st.depression,
  ecg.twi = ecg.twi,
  presentation_hstni = presentation_hstni,
  second_hstni = second_hstni,
  classify = FALSE
)

Arguments

Age

a numeric vector of age values, in years

Gender

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

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

sweating

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

pain.radiation

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

pleuritic

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

palpation

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

ecg.st.depression

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

ecg.twi

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

presentation_hstni

a continuous numeric vector of the troponin levels

second_hstni

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

classify

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

Value

A vector with EDACS 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))
)

# Call the function with the cohort_xx

results <- cohort_xx %>% rowwise() %>% mutate(EDACS_score = EDACS(Age,
Gender, diabetes, smoker, hypertension, hyperlipidaemia, family.history,
sweating, pain.radiation, pleuritic, palpation, ecg.st.depression, ecg.twi,
presentation_hstni, second_hstni, classify = FALSE))