Paper Title: Smart phone based “heart attack” risk prediction; innovation of clinical and social approach for preventive cardiac health

Abstract:

Objectives:

To develop a risk factor based approach to predict risk of developing Heart Attack by using smart phone technology. To initiate a social activity “Check yourself before event”.
Methods:

A prototype software (Android) was developed by integrating clinical data obtained from 506 patients admitted in a cardiac hospital irrespective of final diagnosis. Data was correlated & analysed with presence of ischemic heart disease (IHD). Risk factors like,Hypertension,Diabetes,Dyslipidemia,Smoking,Family History,Obesity,Stress & existing clinical symptoms suggesting sub-clinical or non detected IHD were considered. The data was mined with Data Mining technology and a score was generated. The risk was classified into Low, Medium and High for IHD as per the score. App was tested prospectively with 89 participants with acute coronary syndrome (ACS)
Results:

On comparing patients whose data was obtained for generating the score;we found there is a significant correlation of having a cardiac event when low and high category was compared;p = 0.0001. Among patients categorized into high;83.9 % had IHD while in low category,only 12.5%. The difference between medium and high was also significant with p = 0.0001. In a prospective observation among those who presented to hospital with ACS, 86.69 % patients had high scores.
Conclusion:

Our research is motivated to make simple & social approach to predict the IHD risk and aware individuals to get evaluated. Currently available tools are underutilized by population;Our mobile application may reduce this limitation and promote a risk evaluation on time. Based on data collection,we aim to develop”Help Centers” for high risk individuals to aware them on cardiac health and guide them for evaluation.