ArticleJournal of the American College of Cardiology2025
AHA PREVENT Equations and Cardiovascular Disease Risk in Diverse Health Care Populations.
Article in Journal of the American College of Cardiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- The PREVENT Risk Equations and Cardiovascular Prevention in East Asia.Journal of atherosclerosis and thrombosis · 2026Review
- Development and Validation of a Clinical Polygenic Risk Report in U.S.-Based Health Systems for 8 Cardiovascular Conditions.Journal of the American College of Cardiology · 2026Article
- Three-year cardiovascular risk prediction among people who use cocaine or methamphetamine.Drug and alcohol dependence reports · 2026Article
- Review
- Cardiovascular disease in women: traditional and sex-specific risk factors.European heart journal · 2026Review
- Impact of PREVENT Cardiovascular Risk Equations on Statin Eligibility by Subgroup and Risk Thresholds: A Cross-Sectional Study.Journal of general internal medicine · 2026Article
- Reply: Underestimation of Risk or Overascertainment of Events in Assessing Risk Prediction Equations?Journal of the American College of Cardiology · 2026Article
- Artificial intelligence-based quantification of breast arterial calcifications to predict cardiovascular morbidity and mortality.European heart journal · 2026Article
- Aortic and Cardiac Structure From Routine CT Predict Cardiovascular Risk Beyond PREVENT and Coronary Calcium.JACC. Cardiovascular imaging · 2026Article
- Validation and Recalibration of PCE, China-PAR, and PREVENT Models for Estimating ASCVD Risk in China.JACC. Asia · 2026Article
- Glycaemic variability underlies myocyte dysfunction and myocardial injury risk in diabetes.Nature communications · 2026Article
- Performance of PREVENT Cardiovascular Risk in Electronic Health Record-Based Clinical Practice.JAMA network open · 2026Article
- Multiomics for Risk Stratification in Atherosclerotic Cardiovascular Disease.Circulation. Genomic and precision medicine · 2026Review
- CARDIAC-FM: A Multimodal Foundation Model for Cardiovascular Risk Prediction Using ECG and Cardiac MRI.medRxiv : the preprint server for health sciences · 2026Article
- Bridging the Gap in Racial/Ethnic Disparities: Perspectives from the 2025 American Heart Association/American College of Cardiology High Blood Pressure Guideline.Current hypertension reports · 2026Review
- Investigating the causal relationship between diabetes and shoulder periarthritis: A 2-sample Mendelian randomization study.Medicine · 2026Article
- Bundled measurement of LDL-cholesterol, lipoprotein(a), and high sensitivity C-reactive protein across the spectrum of cardiovascular risk.American journal of preventive cardiology · 2026Article
- Environment and CVD: moving from Risk Prediction to Risk Management.Current atherosclerosis reports · 2026Review
Corrections and comments
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Authors and funding
17 authors.
Funding
Abstract
backgroundThe American Heart Association's Predicting Risk of cardiovascular Events (PREVENT) aims to improve cardiovascular risk prediction. Whether PREVENT suitably predicts 10-year incident atherosclerotic cardiovascular disease (ASCVD) in health care populations is unknown.
objectivesThis study sought to evaluate the calibration and discrimination of the PREVENT equations across integrated U.S. health care systems.
methodsWe retrospectively evaluated electronic health records of 270,320 patients (Mass General Brigham [MGB]: 136,654; Mount Sinai Health: 43,321; Penn Medicine: 56,889; Vanderbilt University Medical Center: 33,456) aged 30 to 79 years and without prior ASCVD from 2010 to 2014. We compared 10-year estimated ASCVD risk based on PREVENT and empirically observed first ASCVD event over a 10-year follow-up. Calibration was assessed based on Greenwood-Nam-d'Agostino test, discordance, and mean calibration. Discrimination was assessed with the use of the time-dependent Harrell's C-index.
resultsBased on PREVENT, the mean estimated 10-year ASCVD risk was 4.9% ± 4.7% in MGB (mean age 54 years, 42% female), 6.0% ± 5.6% in Mount Sinai (mean age 56 years, 54% female), 6.0% ± 5.2% in Penn (mean age 58 years, 55% female), and 4.8% ± 1.3% in Vanderbilt (mean age 60 years, 51% female). Although PREVENT underestimated the observed incidence rate in MGB (discordance: -71.0%), Mount Sinai (discordance: -36.2%), and Vanderbilt (discordance: -40.0%), it more closely mirrored the empirical rate in Penn (+1.3%). Overall, PREVENT yielded moderate discrimination C-index in MGB (0.70 [95% CI: 0.70-0.70]), Mount Sinai (0.74 [95% CI: 0.73-0.75]), Penn (0.69 [95% CI: 0.68-0.70]), and Vanderbilt (0.73 [95% CI: 0.72-0.74]). Nevertheless, calibration differed by sex, with greater underestimation among women in MGB (discordance: -80.7%) and Vanderbilt (discordance: -55.5%) but among men in Mount Sinai (discordance: -40.7%). The race and ethnicity-stratified predictive performance varied across health care systems. Compared with the pooled cohort equations, PREVENT demonstrated better overall calibration in Penn (+2.5% vs +93.6%) but worse in MGB (-70.0% vs -41.6%) and Mount Sinai (-36.4% vs 4.8%), notwithstanding comparable discrimination. The PREVENT predictive performance further differed with better discrimination among patients without diabetes mellitus or antihypertensives.
conclusionsThe PREVENT model moderately discriminated ASCVD incidence across 4 geographically distinct academic health care systems in the United States. However, calibration metrics varied widely across health care systems, sociodemographics, and underlying cardiometabolic comorbidities.
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