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

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 thatwas 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.