Primary purpose of this app is to estimate an individual’s 10-year risk for a first hard atherosclerotic cardiovascular disease (ASCVD) among patiens without pre-existing cardiovascular disease.
- formula used in the risk calculations were from pooled cohort equations,
- this app allows for changing risk factors, and immediately recalculats the risk. For example, for a smoker, giving up smoking provides a risk reduction, and clicking corresponding option results to change in the risk estimate. Thats displayed instantly,
- an individual can assess the risk factor and see if he/she should make lifestyle changes to reduce the risk of getting atherosclerotic cardiovascular disease.
Risk of getting cardiac event during the Assessment of Cardiovascular Risk Full Work Group Report is available to view here: url(http://jaccjacc.cardiosource.com/acc_documents/2013_FPR_S5_Risk_Assesment.pdf)
Pooled cohort equations and required coefficients to perform the risk assesment were obtained from that report. Similar calculators are available online. For example: url(http://clincalc.com/Cardiology/ASCVD/PooledCohort.aspx). This can be used to compare risk estimates to this app results.
For example, for 55 years old white male, with 120 mmHg untreated systolic blood pressure, 50 mg/dL HDL and 213 mg/dL total cholesterol, no diabetes, no smoking, the risk of getting disease during the next 10-years is:
dat<-read.table("table.dat", row.names=1)
const<-dat[3,]
smokc<-0; smokcov<-0; BPc<-const$ln_untreated_BP; BPcov<-0; diab<-0
age<-55; numTC<-213; hdl<-50; numBP<-120
calc<-log(age)*const$ln_age+log(age)*log(age)*const$ln_age_squared+
log(numTC)*const$ln_total_cholest+log(age)*log(numTC)*const$ln_age_totcholest+
log(hdl)*const$ln_hdlC+log(age)*log(hdl)*const$ln_age_hdlC+smokc+
smokcov*log(age)*const$ln_age_smoker+log(numBP)*BPc+log(age)*log(numBP)*BPcov+diab
ASCVD<-round(100*(1-(const$baseline^exp(calc-const$meancoef))),2)
ASCVD## [1] 5.38To run app three files are needed: - table.dat, containing coefficients for equations - server.R, provides calculations for results - ui.R, provides user interface for the app
To run app download all three files to working directory and run two comands in R:
library(shiny)
runApp()Files available here url(https://github.com/GintasBu/data_products.git)