ArticleNature medicine2025
Performance of the American Heart Association's PREVENT risk score for cardiovascular risk prediction in a multiethnic population.
Article in Nature medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Risk Assessment in Cardiovascular-Kidney-Metabolic Syndrome: An Opportunity to Individualize Evidence-Based Therapy in CKD.Clinical journal of the American Society of Nephrology : CJASN · 2026Article
- The PREVENT Risk Equations and Cardiovascular Prevention in East Asia.Journal of atherosclerosis and thrombosis · 2026Review
- Validation of the Predicting Risk of Cardiovascular Disease EVENTs (PREVENT) Equations in a CKD Population: A Nationwide Veterans Analysis.Clinical journal of the American Society of Nephrology : CJASN · 2026Article
- Beyond LDL-C: Modern Lipid Management for ASCVD Prevention in Primary Care.Cardiology and therapy · 2026Review
- The therapeutic approach to cardiovascular-kidney-metabolic syndrome.Nature reviews. Nephrology · 2026Review
- Primary Prevention of Dyslipidemia: 10 Practice-Changing Takeaways from the 2026 ACC/AHA Multisociety Guideline.Current atherosclerosis reports · 2026Review
- Validation and Recalibration of PCE, China-PAR, and PREVENT Models for Estimating ASCVD Risk in China.JACC. Asia · 2026Article
- Risk stratification using coronary artery calcium and potential benefit of semaglutide therapy: A cost-effectiveness modelling study.Diabetes, obesity & metabolism · 2026Article
- Cardiovascular risk stratification without recalibration: A comparative study of the PREVENT and WHO risk scores in a multiethnic Brazilian cohort.American journal of preventive cardiology · 2026Article
- Advances in risk prediction and treatment strategies for CKM syndrome.Nature reviews. Nephrology · 2026Article
- Socioeconomic and Engagement Barriers to Cardiovascular Risk Awareness Among Cancer Survivors.Research square · 2026Article
- The C-reactive protein-triglyceride glucose index (CTI) predicts mortality in cardiovascular-kidney-metabolic syndrome: a dual-cohort study with machine learning validation.International journal of surgery (London, England) · 2026Article
- Metabolic dysfunction-associated steatotic liver disease and heart failure with preserved ejection fraction: mechanisms and clinical implications from a heart-liver metabolic axis perspective.Frontiers in pharmacology · 2026Review
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Authors and funding
13 authors.
Funding
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Abstract
The Predicting Risk of Cardiovascular EVENTS (PREVENT) equations, created and endorsed by the American Heart Association, provide cardiovascular risk estimates for the general population, but have not yet been tested in multiethnic populations. In the present study, in a large nationwide multiethnic sample of US veterans, the utility of PREVENT to predict the risk of total cardiovascular disease (CVD: fatal and nonfatal myocardial infarction, stroke or heart failure; PREVENT-CVD), atherosclerotic cardiovascular disease (ASCVD: fatal and nonfatal myocardial infarction or stroke; PREVENT ASCVD) and heart failure was evaluated. We assessed the discrimination and calibration performance of ASCVD prediction with PREVENT ASCVD compared with a previous risk-prediction score, pooled cohort equations (PCEs). Among 2,500,291 veterans aged 30-79 years (93.9% men and 6.1% women), 407,342 total CVD events occurred over a median (interquartile range (IQR)) follow-up of 5.8 (IQR = 3.1-8.3) years. The Concordance index (C-index) (95% confidence interval (CI)) for PREVENT-CVD was 0.65 (95% CI = 0.65-0.65) in the overall sample and was similar across different race and ethnic groups (Asian, Native Hawaiian or Pacific Islander, 0.70 (95% CI = 0.69-0.71); Hispanic, 0.70 (95% CI = 0.69-0.70); non-Hispanic Black. 0.68 (95% CI = 0.68-0.69) and non-Hispanic White, 0.65 (95% CI = 0.64-0.65)). C-indices were similar between PREVENT ASCVD and PCEs and ranged from 0.61 to 0.63. Calibration slopes for PREVENT-CVD and -ASCVD in the overall sample were 1.09 (s.e. = 0.04) and 1.15 (s.e. = 0.04), respectively. In contrast, PCEs demonstrated overprediction for ASCVD with a calibration slope of 0.51 (s.e. = 0.06). Calibration slopes for PREVENT and PCEs were similar across race and ethnic groups. Among US veterans, the PREVENT equations accurately estimated CVD and ASCVD risk with some variability across race and ethnicity groups and outperformed PCEs for ASCVD risk prediction.
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