Comparison of ASCVD Risk Prediction Models in STEMI: Insights From a South Asian Cohort.
Most Indian acute myocardial infarction 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 (cardiovascular) 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 (atherosclerotic cardiovascular disease) risk prediction models in first acute myocardial infarction (acute myocardial infarction).
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 Framingham Risk Score, 15.0% using World Health Organization charts, 11.7% using JBS-3, and 12.3% using atherosclerotic cardiovascular disease 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 atherosclerotic cardiovascular disease, κ = 0.311; 95% CI: 0.288-0.33 with Framingham Risk Score, and κ = 0.063; 95% CI: 0.038-0.088 with World Health Organization), despite moderate positive correlations.
Major cardiovascular risk algorithms classify Indian acute myocardial infarction patients very differently, with substantial potential for misclassification.
Although PREVENT and Framingham Risk Score 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.