ArticleJACC. Advances2024
PREVENT and Pooled Cohort Equations in Mortality Risk Prediction: National Health and Nutrition Examination Survey.
Article in JACC. Advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07502703 (Validation of Remote Photoplethysmography), which is not on this map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Validation of Remote Photoplethysmography (rPPG)-Derived Cardiovascular Parameters Against Standard Clinical Measurements and Risk Scores in a Community-Based Population in Semanan, Jakarta
Who cites it
6 citing papers in PubMed.
- Association between thyroid function and 10-year cardiovascular disease risk of patients with diabetes: a cross-sectional study using KNHANES 2013-2014.Journal of Yeungnam medical science · 2026Article
- Cardiovascular disease risk estimates using the new PREVENT Equation: The good, bad, and the ugly.American journal of preventive cardiology · 2025Review
- LDL-C targets based on coronary artery calcium: advancing Figure 6 from the 2022 American college of cardiology expert consensus decision pathway.American journal of preventive cardiology · 2025Article
- Atherosclerotic Cardiovascular Disease Risk Estimates Using the New Predicting Risk of Cardiovascular Disease Events Equations: Implications for Statin Use.Current cardiology reports · 2025Review
- Atherosclerotic Cardiovascular Disease Risk Estimates Using the New Predicting Risk of Cardiovascular Disease Events Equations: Implications for Statin Use.Current cardiology reports · 2025Review
- PREVENT Risk Score vs the Pooled Cohort Equations in MESA.JACC. Advances · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Background: The Predicting Risk of CVD Events (PREVENT) equations were developed to address limitations of the Pooled Cohort Equations (PCEs) in predicting atherosclerotic cardiovascular disease (ASCVD) risk. The comparative effectiveness of the PREVENT equations versus the PCEs in predicting mortality risk remains unknown. Objectives: The purpose of this study was to compare the risk discrimination value of the PREVENT equations with the PCEs for predicting mortality. Methods: This retrospective cohort study included individuals aged 40 to 79 years, free of cardiovascular disease, from the National Health and Nutrition Examination Survey (1999-2004). The outcomes of interest were all-cause and cardiovascular mortality. Harrell's C-statistics was used to examine risk discrimination. Results: In this study, including 4,342 individuals (median age: 50.3 [IQR: 44.3-59.6] years, 51.5% females, and 77.0% non-Hispanic White), the median 10-year ASCVD risk was 4.0% (IQR: 1.5%-9.9%) using the PCEs and 2.4% (IQR: 1.2%-5.3%) using the PREVENT equations. The PREVENT equations generated lower ASCVD risk estimates in 81.0% (79.4%-82.6%) of individuals relative to the PCEs, with the lower estimates disproportionately affecting males (97.7% [96.6%-98.8%]) and Black individuals (89.6% [87.3%-91.8%]). Using a 5.0% risk threshold, PREVENT and PCEs classified 26.7% (∼16.9 million U.S. individuals) and 43.4% (∼27.5 million U.S. individuals), respectively, as having a 10-year ASCVD risk >5%. Among the 10.2% classified as high risk by the PCEs, 96.2% were reclassified to a lower risk by PREVENT. The risk discrimination value for all-cause and cardiovascular mortality was similar using the PREVENT equations and the PCEs. Conclusions: The PREVENT equations provide similar risk discrimination values for mortality compared to the PCEs but estimate lower 10-year ASCVD risk. Replacing PCEs with the PREVENT equations could reduce statin eligibility in a significant number of individuals.
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