Comparison of ASCVD Risk Prediction Models in STEMI: Insights From a South Asian Cohort.
Most Indian AMI patients are not identified as high risk by current models.
Comparison of ASCVD Risk Prediction Models in STEMI: Insights From a South Asian Cohort.
Cardiovascular (CV) risk prediction models guide primary prevention, yet most were derived in Western populations and may not generalize to the South Asian population.
To compare risk classification, agreement, and discriminative patterns of major atherosclerotic cardiovascular disease (ASCVD) risk prediction models in first acute myocardial infarction (AMI).
Were categorized as low (<7.5%), intermediate (7.5% to <20%), or high (≥20%) risk.
PREVENT classified 19.8% of patients as high risk, compared with 20.2% using FRS, 15.0% using WHO charts, 11.7% using JBS-3, and 12.3% using ASCVD 2013.
PREVENT demonstrated the widest risk distribution (0.2%-91%).
Agreement between PREVENT and other models was poor (κ = 0.228; 95% CI: 0.204-0.252 with ASCVD, κ = 0.311; 95% CI: 0.288-0.33 with FRS, and κ = 0.063; 95% CI: 0.038-0.088 with WHO), despite moderate positive correlations.
Major CV risk algorithms classify Indian AMI patients very differently, with substantial potential for misclassification.
Although PREVENT and FRS showed nearly similar classification of high risk, 80% of patients were still not identified as high risk before their event, underscoring the need for South Asia-specific risk score development and validation and alternative preventive strategies.