EDACS score function for data frame; EDACS = Emergency Department Assessment of Chest Pain Score
Source:R/04_EDACS_df.R
EDACS_scores.Rd
This function allows you to calculate the EDACS 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
EDACS_scores(
data,
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
)
Arguments
- data
A data frame with all the variables needed for calculation: Age, Gender, diabetes, smoker, hypertension, hyperlipidaemia, family.history, sweating, pain.radiation, pleuritic, palpation, ecg.st.depression, ecg.twi, presentation_hstni, second_hstni, classify
- 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
data frame with two extra columns including the 'EDACS_score' calculations and their classifications, 'EDACS_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))
)
# Call the function with the cohort_xx
result <- EDACS_scores(data = cohort_xx, classify = TRUE)
summary(result$EDACS_strat)
#> Low risk Not low risk
#> 1 99
summary(result$EDACS_score)
#> Min. 1st Qu. Median Mean 3rd Qu. Max.
#> -3.00 4.75 10.00 10.18 14.25 25.00