Evidence map›Paper›PMID 40316142›Full record

ArticleClinical medicine (London, England)2025

Validation of ARIC heart failure risk score in an Asian population: Results from the CORE-Thailand registry.

Nichanan Osataphan, Ply Chichareon, Wanwarang Wongcharoen, Krit Leemasawat, Narawudt Prasertwitayakij, Pannipa Suwannasom, Siriluck Gunaparn, Kasem Rattanasumawong, Rungroj Krittayaphong, Arintaya Phrommintikul and 1 more

Abstract readValidation Study
In one paragraph

Article in Clinical medicine (London, England), 2025. 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

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

1 citing paper in PubMed.

  1. 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

11 authors.

Nichanan OsataphanDivision of Cardiology, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Ply ChichareonCardiology unit, Division of Internal Medicine, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand.
Wanwarang WongcharoenDivision of Cardiology, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Krit LeemasawatDivision of Cardiology, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Narawudt PrasertwitayakijDivision of Cardiology, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Pannipa SuwannasomDivision of Cardiology, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Siriluck GunaparnDivision of Cardiology, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Kasem RattanasumawongPolice General Hospital, Bangkok, Thailand.
Rungroj KrittayaphongDivision of Cardiology, Department of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Arintaya PhrommintikulDivision of Cardiology, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand. Electronic address: arintaya.p@cmu.ac.th.
CORE-Thailand investigators

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe Atherosclerotic Risk in Communities (ARIC) heart failure (HF) score was originally developed in the USA to predict new-onset HF. Our goal was to validate the ARIC-HF score and develop a new score to predict HF in an Asian population.

methodsThe Cohort Of patients with high Risk for cardiovascular Events (CORE-Thailand) was a prospective registry of Thai patients with high atherosclerotic risk. Patients were followed for 5 years for HF events. The ARIC-HF score was applied to predict HF. The new ARIC-CORE score was developed by re-estimating the coefficients of ARIC score variables using ridge regression. The discrimination and calibration of the models were assessed. The net reclassification index (NRI) was used to compare the prediction performance between the models. Clinical utility was assessed with a decision curve analysis.

resultsFrom a total of 8,919 patients, 185 (2.1 %) developed HF. The ARIC-HF score and ARIC-CORE HF risk score provided good discrimination with C-statistics of 0.710, (95 % confidence interval (CI); 0.673-0.747) and 0.75, (95 % CI; 0.715-0.785), respectively. Both models showed a good calibration. Using the ARIC-CORE HF score was associated with an improved reclassification of HF (NRI 0.369, 95 % CI; 0.286-0.551) compared to the ARIC-HF score. The net clinical benefit of the ARIC-CORE HF score was higher than the ARIC-HF score in the decision curve analysis.

conclusionThe ARIC-HF score performed well in predicting heart failure in the CORE population. The ARIC-CORE HF score showed superior predictive ability and clinical benefit. Further research is needed to validate these models in diverse Asian populations.

Indexed as

Heart FailureAgedAsian PeopleFemaleHumansMaleMiddle AgedProspective StudiesRegistriesRisk AssessmentRisk FactorsThailandARICHeart failurePredictive model

Identifiers

PMID40316142
PMCPMC12145831

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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.