Prediction of Ischemic Heart Diseases using Logistic Regression a Case-Control Study

Abstract

The present study was designed to identify the level of Ischemic Heart
Disease (IHD) with reference to various risk factors. This was a case-control study that
was used to develop a predictive model for the risk of IHD in various conditions.
Complete information of 980 males and females was taken at the Punjab Institute of
Cardiology Lahore. 480 patients and 480 healthy individuals were taken as
experimental and control group respectively. Data was examined through SPSS
version 17. The age of the patient was shown in the manner of Mean ± Standard Error.
To estimate the chances of Ischemic Heart Disease, Step-by-step Logistic Regression
Framework was utilized. An average age was recorded as 49.73 ± 0.47 among all the
individuals. There were 63.5 percent of males and 36.5 percent of females were
included in this study. In present investigation, age, obesity, blood glucose level, way of
living, perspiration, cough, dizziness and high blood pressure were found to promote
the development of IHD. This study showed IHD model has more prediction power
with age and lower economic condition. Certain conditions such as high blood
pressure, diabetes, and chest pains greatly exacerbate the condition. Men were at
greater risk of IHD as compared to women.