Cardiovascular disease risk estimates using the new PREVENT Equation: The good, bad, and the ugly.

Pooja V Selvam, Rahul Sharma, Peter Ganz, Roger S Blumenthal, Martha Gulati

Abstract readReview

In one paragraph

Review in American journal of preventive cardiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it

0cells of the map it votes in

6citing 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

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

Cardiovascular disease in women: traditional and sex-specific risk factors.European heart journal · 2026
Review
The ABCs of cardiovascular disease prevention: communicating what we know in 2026.American journal of preventive cardiology · 2026
Review
Advancing Cardiovascular Risk Stratification in Asian Populations: Opportunities and Remaining Gaps.JACC. Asia · 2026
Article
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 · 2026
Review
AI-powered retinal imaging for early ASCVD risk stratification in a hybrid care model: preliminary findings from SAFER.Frontiers in artificial intelligence · 2026
Article
Can QRISK-3 and PREVENT Predict Premature Acute Coronary Syndrome in Adults under 40 Years? The Insights from Predicting the Risk of Acute Coronary Syndrome under 40 (PRACS-40) Study.Heart views : the official journal of the Gulf Heart Association
Article

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Pooja V SelvamDepartment of Internal Medicine, Johns Hopkins Bayview Medical Center, Baltimore, MD, USA.

Rahul SharmaDepartment of Internal Medicine, Greater Baltimore Medical Center, Baltimore, MD, USA.

Peter GanzDivision of Cardiology, University of California San Francisco, San Francisco, CA, USA.

Roger S BlumenthalCiccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Martha GulatiBarbra Streisand Women's Heart Center, Smidt Heart Institute at Cedars Sinai Medical Center, Los Angeles, California and The Baim Institute for Clinical Research, Boston, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Cardiovascular diseasePreventive cardiologyRisk assessment

Identifiers

PMID41018255

DOI10.1016/j.ajpc.2025.101288

PMCPMC12464685

What Socratic holds

Textmetadata

LicenceCC BY-NC-ND

Read underepoch 390

Registered trials

None linked

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 Socratic graph.