Evidence mapPaperPMID 41216256Full record

ArticleCardiovascular diagnosis and therapy2025

Non-alcoholic fatty liver disease as a predictor of atrial fibrillation recurrence following ablation: a retrospective study.

Zhe Wang, Fangyuan Luo, Yuekun Zhang, Yafei Zhai, Xiaojie Chen, Liping Sun, Yingwei Chen

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Article in Cardiovascular diagnosis and therapy, 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

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Zhe WangDepartment of Cardiology, Beijing Anzhen Hospital, Capital Medical University, National Clinical Research Center for Cardiovascular Diseases, Beijing, China.
Fangyuan LuoDepartment of Cardiology, China-Japan Friendship Hospital (Institute of Clinical Medical Sciences), Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Yuekun ZhangDepartment of Cardiology, Beijing Anzhen Hospital, Capital Medical University, National Clinical Research Center for Cardiovascular Diseases, Beijing, China.
Yafei ZhaiDepartment of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Xiaojie ChenDepartment of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Liping SunDepartment of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Yingwei ChenDepartment of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Epidemiological evidence suggests an association between non-alcoholic fatty liver disease (NAFLD) and incident atrial fibrillation (AF); however, the magnitude of this association and its prognostic value in predicting the recurrence of AF after radiofrequency catheter ablation (RFCA) have not been fully characterized. The present study was designed to elucidate the complex interplay between NAFLD and the risk of AF recurrence after ablation. Methods: A total of 1,182 patients with AF who underwent initial RFCA from June 2018 to December 2022 at the First Affiliated Hospital of Zhengzhou University were included in this retrospective cohort study. The Kaplan-Meier method was used to plot AF recurrence curves after ablation. Multivariable Cox models were then used to examine the associations between NAFLD and the recurrence of AF. Analyses were also conducted to assess whether the predictive effect of NAFLD was consistent across different subgroups. Results: Over a 1-year follow-up period, 30.1% of the patients experienced recurrent AF. The multivariable Cox analysis revealed that NAFLD was an independent risk factor for the recurrence of AF after controlling for model 2 (hazard ratio =1.37, 95% confidence interval: 1.10-1.70, P=0.005). These correlations remained statistically significant across various models. Further, incorporating NAFLD in the fully adjusted basic risk model significantly increased the ability of the model to predict AF recurrence, with the C-statistic increasing from 0.672 to 0.686 (P=0.03). Additionally, diabetes mellitus (DM) (P value for interaction =0.049) and female sex (P value for interaction =0.02) had a statistically significant interactive effect with NAFLD in predicting the recurrence of AF. Conclusions: NAFLD was found to be independently associated with the recurrence of AF after ablation. Moreover, the AF recurrence rate after RFCA was higher in the NAFLD patients who had DM or were female. The study showed that NAFLD may serve as a dependable marker for assessing AF recurrence risk in clinical practice.

Indexed as

Atrial fibrillation (AF)non-alcoholic fatty liver disease (NAFLD)radiofrequency ablationrecurrence

Identifiers

PMID41216256
PMCPMC12596445

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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 Socratic graph.