Evidence map›Paper›PMID 40999261›Full record

ArticleJournal of general internal medicine2026

Impact of PREVENT Cardiovascular Risk Equations on Statin Eligibility by Subgroup and Risk Thresholds: A Cross-Sectional Study.

Aileen P Wright, Allison B McCoy, Kimberly Garcia, Peter J Embí, Walter K Clair, MacRae F Linton, Adam T Wright

Abstract read
In one paragraph

Article in Journal of general internal medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Observational
4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Aileen P WrightDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA. aileen.p.wright.1@vumc.org.ORCID 0000-0002-7550-4284
Allison B McCoyDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.
Kimberly GarciaDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.
Peter J EmbíDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.
Walter K ClairDivision of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
MacRae F LintonDivision of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
Adam T WrightDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.

Funding

Non-coding RNA & Bioinformatics CoreP01HL116263 · NHLBI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI LINTON, MACRAE F · 2014 to 2025
$24.7M
Artificial Intelligence-Assisted Clinical Decision Support for Preventing Hypoglycemia in Hospitalized PatientsK23DK136974 · NIDDK · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Aileen Wright · 2024 to 2026
$474k
NHLBI NIH HHS HL116263NHLBI NIH HHS P01 HL116263NIDDK NIH HHS K23 DK136974NIDDK NIH HHS K23DK136974-02
6 · The paper itself

Abstract

backgroundReplacing the pooled cohort equations (PCEs) with the Predicting Risk of Cardiovascular Disease EVENTs (PREVENT) equations for atherosclerotic cardiovascular disease (ASCVD) risk is projected to reduce statin eligibility, prompting discussion of lowering the risk threshold used with PREVENT. The potential impact on statin eligibility in different subgroups is unknown.

objectiveTo assess the impact of replacing PCEs with PREVENT equations on statin eligibility for a real-world population of primary care patients, incorporating social deprivation index (SDI) and lowering the ASCVD risk thresholds for statin eligibility.

designCross-sectional analysis comparing 10-year ASCVD risk scores and statin eligibility using the PCEs and PREVENT equations within a primary care population. Subgroup analyses were conducted by age, sex, and race. Risk thresholds for statin eligibility were varied to assess the effect on eligibility.

participantsAdult patients who visited a Vanderbilt primary care clinic in 2023. MAIN MEASURES: Estimated 10-year ASCVD risk and proportion of patients eligible for statin therapy using the PCEs vs. PREVENT equations. KEY

resultsIn 50,123 patients, the mean 10-year ASCVD risk was significantly lower with PREVENT compared to the PCEs (3.6 vs. 7.5, p < 0.0001). In 36,430 patients not on statins, PREVENT reduced statin eligibility by 78.2%, with the largest reductions in women (82.6%), patients aged 40-49 (97.8%), and Black patients (81.2%). Lowering the statin eligibility threshold from 7.5 to 3% led to a 27.5% overall increase in eligibility rather than 78.2% reduction. However, gaps between subgroups expanded, and younger and Black patients retained relative reductions in eligibility (e.g., 4.7% decrease in statin eligibility among Black patients compared to a 32.7% increase among White patients).

conclusionsIn a real-world primary care population, replacing the PCEs with the PREVENT equations would significantly reduce statin eligibility at the 7.5% threshold. Lowering the risk threshold would increase overall eligibility but disproportionately affect eligibility within certain subgroups.

Indexed as

Cardiovascular DiseasesEligibility DeterminationHydroxymethylglutaryl-CoA Reductase InhibitorsAdultAgedCross-Sectional StudiesFemaleHeart Disease Risk FactorsHumansMaleMiddle AgedRisk AssessmentHydroxymethylglutaryl-CoA Reductase Inhibitorsatherosclerotic cardiovascular diseasepreventionrisk prediction modelssocial deprivation indexstatins

Identifiers

PMID40999261
PMCPMC13241340

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.