P129 ASSESS THE ACCURACY OF FOUR RISK ASSESSMENT MODELS (RISKFRS, RISKWHO, RISKACC/AHA, AND RISKJBS) IN PREDICTING 10-YEAR CARDIOVASCULAR EVENT RISK IN INDIAN ACUTE MYOCARDIAL INFARCTION PATIENTS

Background: Despite numerous risk assessment models available for estimating the 10-year risk of cardiovascular (CV) events in individuals requiring primary prevention of CV disease, their applicability and accuracy in the Indian population remain inadequately studied. Objective of the study is to Assess and compare the predictive accuracy of four cardiovascular risk assessment models—RiskFRS, RiskWHO, RiskACC/AHA, and RiskJBS—in determining the 10-year cardiovascular event risk among Indian acute MI patients. Methods: In this study, 250 participants (mean age 59.4 ± 10.6 years; 205 males) without prior cardiovascular disease who experienced acute myocardial infarction (MI) were assessed using four established risk assessment models: Framingham Risk Score (RiskFRS), World Health Organization risk prediction charts (RiskWHO), American College of Cardiology/American Heart Association pooled cohort equations (RiskACC/AHA), and the 3rd Joint British Societies’ risk calculator (RiskJBS). These models estimated the participants’ predicted 10-year risk of cardiovascular events if assessed before the acute MI. Results: RiskWHO provided the lowest risk estimates, with 86.6% of patients estimated to have less than 20% 10-year risk. Conversely, RiskFRS and RiskACC/AHA yielded higher risk estimates (61.7% and 69.8% with less than 20% risk, respectively; p values <0.001 compared to RiskWHO). However, RiskJBS identified the highest proportion of patients as high-risk (only 44.1% at less than 20% risk, p values < 0.01 compared to all other three risk scores). Conclusions: In Indian patients experiencing acute MI, RiskJBS identifies a larger proportion of patients as ’high-risk’ compared to RiskWHO, RiskFRS, and RiskACC/AHA. However, further validation through large-scale prospective studies is necessary. These findings underscore the importance of tailoring risk assessment models to the unique characteristics of the Indian population and highlight the need for additional research to optimize cardiovascular risk prediction and management strategies in this demographic.