Evidence map›Paper›PMID 41436937›Full record

ArticleBMC cardiovascular disorders2025

Construction and validation of a predictive model for the risk of atrial fibrillation in patients with heart failure with preserved ejection fraction: a single-center retrospective analysis.

Pan Chen, Xiaoyan Yin, Lei Ren

Abstract readValidation Study
In one paragraph

Article in BMC cardiovascular disorders, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

What it found

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Pan ChenAnhui Medical University Affiliated Fuyang People's Hospital, Fuyang People's Hospital, Fuyang, Anhui, 236000, China.
Xiaoyan YinBengbu Medical University Affiliated Fuyang Hospital, Fuyang People's Hospital, Fuyang, Anhui, 236000, China.
Lei RenAnhui Medical University Affiliated Fuyang People's Hospital, Fuyang People's Hospital, Fuyang, Anhui, 236000, China. renlei7598@163.com.

Funding

2021 Anhui Provincial Health Commission Scientific Research Project AHWJ2021b0702024 Fuyang City Key Research and Development Program Project FK20245514
6 · The paper itself

Abstract

backgroundTo explore the risk factors for atrial fibrillation (AF) in patients with heart failure with preserved ejection fraction (HFpEF) and to construct a predictive model for AF in this population.

methodApproximately 334 patients with HFpEF who were treated in the Department of Cardiology at Fuyang People's Hospital from January 2022 to April 2024 were included. Patients were followed up for one year to observe whether they developed AF. All patients were randomly divided into a training set and a validation set in a 7:3 ratio, with the training set used for model construction and the validation set used for model performance evaluation. The Boruta algorithm was used for feature selection, and a predictive model was constructed using multivariate logistic regression analysis. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), Hosmer-Lemeshow goodness-of-fit test, calibration curve, and decision curve analysis (DCA).

resultsLogistic regression analysis revealed that coronary heart disease (CHD), body mass index (BMI), diastolic pressure (DP), free triiodothyronine (FT3), glomerular filtration rate (GFR), and sodium-glucose cotransporter 2 inhibitor (SGLT2i) were independent risk factors for the occurrence of atrial fibrillation in patients with heart failure with preserved ejection fraction (P < 0.05). The AUC was 0.871 in the training set and 0.825 in the validation set; the Hosmer-Lemeshow goodness-of-fit test yielded χ² = 5.3976 (P = 0.7144); decision curve analysis (DCA) indicated that the predictive model could provide superior clinical net benefit for patients with heart failure with preserved ejection fraction.

conclusionA predictive model constructed using six predictive variables-CHD, BMI, DP, FT3, GFR, and SGLT2i-can effectively predict the risk of atrial fibrillation in patients with HFpEF and aid in early risk stratification.

Indexed as

Atrial FibrillationDecision Support TechniquesHeart FailureStroke VolumeVentricular Function, LeftAgedAged, 80 and overChinaFemaleHumansMaleMiddle AgedPredictive Value of TestsPrognosisReproducibility of ResultsRetrospective StudiesAFBoruta algorithmHFpEFPredictive modelSGLT2i

Identifiers

PMID41436937
PMCPMC12729152

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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.