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Updated: Oct 1, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
The PREVENT Equations Evidence Appraisal of Validation and Clinical Implications
Ibrahim Mortada1, Ebrahim Adel Elkolaly2, Aaron W Lee3
1Department of Cardiovascular Medicine, University of Texas Medical Branch, Galveston, Texas, USA.
Abstract:
The American Heart Association's PREVENT equations offer a contemporary, race-free alternative to the Pooled Cohort Equations (PCE), incorporating kidney function to estimate 10- and 30-year risks of atherosclerotic cardiovascular disease (ASCVD), heart failure, and total CVD. PREVENT-ASCVD is now recommended for primary-prevention risk assessment in the 2026 multisociety dyslipidemia guidelines, replacing the PCE, making its real-world performance immediately consequential. PREVENT generally preserves discrimination, but calibration varies across populations, with possible overestimation or underestimation. It often lowers estimated risk and modeled eligibility for statin or antihypertensive therapy versus the PCE. Performance is favorable in several general and older-adult cohorts, but underestimation is concerning in people with HIV, rheumatoid arthritis, selected international cohorts, and statin-naïve adults. Coronary artery calcium can refine selected estimates, though no trial has shown PREVENT-guided care improves outcomes. This narrative review appraises external validation, calibration, and reclassification behavior, evaluates effects on treatment eligibility, and identifies evidence gaps, concluding that implementation should remain population-sensitive with local validation and recalibration when appropriate.
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