Jcvrisk (version 0.1.3)

jals_stroke_wECG: 5-year risk calculation for Stroke based on the JALS study with electrocardiogram model

Description

jals_stroke_wECG() calculates the 5-year probability of developing the stroke event. Mandatory variables: "age", "male", "sbp", "dbp", "t2dm", "smoking", "ht_medication", "af". These variables must be applied with the above spelling.

The details of this prediction model should be referred to the original article. "Absolute risk score for stroke, myocardial infarction, and all cardiovascular disease: Japan Arteriosclerosis Longitudinal Study"

DOI:10.1038/s41440-019-0220-z

PMID:30760890

Usage

jals_stroke_wECG(data)

Value

Based on the mandatory variables, a risk probability will be calculated for each line. The primary cautions are as follows,

1."Data frame must contain the following columns.":

If you contact this warning message, the data frame did not contain required variables. Please check the data frame contain the mandatory variables in the designated spelling.

2."Data frame contains NA values in required columns.":

jals_stroke_wECG() returns the NA if the required variables were missing, or NAs were generated in the calculation process.

3."Some individuals are aged 90 or older. results may not be accurate.":

4."Some individuals are aged 40 or younger. results may not be accurate.":

Arguments

data

A data frame containing the variables to estimate risk.

Examples

data <- data.frame(
  af = c(1, 0, 0, 1, 1, 0),
  sbp = c(110, 125, 135, 150, 170, 180),
  dbp = c(75, 75, 85, 95, 105, 110),
  ht_medication = c(0, 1, 0, 1, 0, 1),
  age = c(39, 49, 59, 69, 79, 80),
  t2dm = c(0, 0, 1, 1, 1, 0),
  male = c(1, 1, 0, 0, 0, 1),
  smoking = c(1, 0, 1, 0, 0, 1)
)

# af            :atrial fibrillation(category: 0 = negative, 1 = positive)
# sbp           :systolic blood pressure(continuous)
# dbp           :diastolic blood pressure(continuous)
# ht_medication :hypertensive medication user(category:0 = non-user,1 = user)
# age           :age(continuous)
# t2dm          :diabetes mellitus(category:0 = non-prevalent DM,1 = prevalent DM)
# male          :male(category:0 = female,1 = male)
# smoking       :smoking status(category:0 = never/past smoker,1 = current smoker)

jals_stroke_wECG(data)