Evidence map›Paper›PMID 42486643›Full record

ReviewJournal of atherosclerosis and thrombosis2026

The PREVENT Risk Equations and Cardiovascular Prevention in East Asia.

Mitsuaki Sawano, Kentaro Ejiri, Yuichiro Mori, Hokyou Lee, Aya Hirata, Kosuke Inoue, Takeshi Kitai, Shun Kohsaka, Hyeon Chang Kim, Kunihiro Matsushita

Abstract readReview
In one paragraph

Review in Journal of atherosclerosis and thrombosis, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Mitsuaki SawanoTeikyo Academic Research Center, Teikyo University.
Kentaro EjiriDepartment of Cardiovascular Medicine, Faculty of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University.
Yuichiro MoriDepartment of Health Promotion and Behavioral Sciences, Graduate School of Medicine, Kyoto University.
Hokyou LeeDepartment of Preventive Medicine, Yonsei University College of Medicine.
Aya HirataDepartment of Preventive Medicine and Public Health, Keio University School of Medicine.
Kosuke InoueDepartment of Health Promotion and Behavioral Sciences, Graduate School of Medicine, Kyoto University.
Takeshi KitaiDepartment of Heart Failure and Transplantation, National Cerebral and Cardiovascular Center.
Shun KohsakaDepartment of Cardiology, Keio University School of Medicine.
Hyeon Chang KimDepartment of Preventive Medicine, Yonsei University College of Medicine.
Kunihiro MatsushitaDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cardiovascular disease remains a leading cause of morbidity and mortality in East Asia, although its epidemiological profile differs substantially from that of Western populations. As East Asia experiences rapid increases in chronic kidney disease, diabetes, multimorbidity, and heart failure driven by population aging, accurate cardiovascular risk prediction has become increasingly important for the risk-stratified prevention of these diseases. Traditional risk prediction models, including the Framingham Risk Score, Pooled Cohort Equations, and SCORE, were derived largely from Western populations and often overestimated the risk in East Asian cohorts without recalibration. In 2025, the American Heart Association introduced the PREVENT equations to estimate 10-year and 30-year risks of total cardiovascular disease, atherosclerotic cardiovascular disease, and heart failure within an integrated cardiovascular-kidney-metabolic framework. Given the growing globalization of cardiovascular prevention and international clinical research, understanding whether PREVENT performs well in East Asian populations has important implications for the clinical implementation and harmonization of risk assessment frameworks. This review summarizes the evolution of cardiovascular risk prediction, key innovations of PREVENT, and emerging validation evidence from East Asia. Early studies from Korea and China suggest the reasonable transportability of these approaches. However, evidence from Japan remains limited, and further validation and recalibration are warranted. We also discuss the challenges related to heart failure prediction, add-on variables, electronic health record data infrastructure, and AI-assisted risk assessment.

Indexed as

Cardiovascular DiseasesAsia, EasternEast Asian PeopleHeart Disease Risk FactorsHumansRisk AssessmentRisk FactorsCardiovascular diseaseCardiovascular-kidney-metabolic syndromeEast AsiaPREVENT equationRisk prediction

Identifiers

PMID42486643
PMCPMC13642998

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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.