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ORIGINAL RESEARCH article

Front. Public Health
Sec. Aging and Public Health
Volume 12 - 2024 | doi: 10.3389/fpubh.2024.1434244
This article is part of the Research Topic Aging and Frailty: From Causes to Prevention View all 7 articles

Nomogram Model for Screening the Risk of Frailty in Elderly Atrial Fibrillation Patients: A cross-sectional study

Provisionally accepted
Hairong Lin Hairong Lin 1Mei Lin Mei Lin 2Zhiying Xu Zhiying Xu 2*Dingce Sun Dingce Sun 1*Hong Li Hong Li 1*
  • 1 Mianyang Central Hospital, Mianyang, China
  • 2 Tianjin Medical University General Hospital, Tianjin, China

The final, formatted version of the article will be published soon.

    Background: Frailty is common in atrial fibrillation (AF) patients, but the specific risk factors contributing to frailty need further investigation. There is an urgent need for a risk prediction model to identify individuals at high risk of frailty. Aims and objectives: This cross-sectional study aims to explore the multiple risk factors of frailty in elderly patients with AF and then construct a nomogram model to predict frailty risk. Methods: We recruited 337 hospitalized patients over the age of 60 (average age: 69, 53.1% male) with AF between November 2021 and August 2022. Data collected included patient demographics, disease characteristics, sleep patterns, mental health status, and frailty measures. We used LASSO and ordinal regression to identify independent risk factors. These factors were then incorporated into a nomogram model to predict frailty risk. The model’s performance was assessed using the concordance index (C-index) and calibration curves. Results: Among the AF patients, 23.1% were classified as frail and 52.2% as pre-frail. Six risk factors were identified: age, gender, history of coronary heart disease, number of chronic conditions, sleep disruption, and mental health status. The internal validation C-index was 0.821 (95% CI: 0.778-0.864; bias-corrected C-index: 0.795), and the external validation C-index was 0.819 (95% CI:0.762-0.876; bias-corrected C-index: 0.819), demonstrating strong discriminative ability. Calibration charts for both internal and external validations closely matched the ideal curve, indicating robust predictive performance. Conclusion: The nomogram developed in this study is a promising and practical tool for assessing frailty risk in AF patients, aiding clinicians in identifying those at high risk. Relevance to clinical practice: This study demonstrates the utility of a comprehensive predictive model based on frailty risk factors in AF patients, offering clinicians a practical tool for personalized risk assessment and management strategies.

    Keywords: Frailty, Atrial Fibrillation, nomogram, sleep disruption, Mental health status, chronic diseases 3120Words, 2tables, 3figures

    Received: 17 May 2024; Accepted: 06 Nov 2024.

    Copyright: © 2024 Lin, Lin, Xu, Sun and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Zhiying Xu, Tianjin Medical University General Hospital, Tianjin, 300052, China
    Dingce Sun, Mianyang Central Hospital, Mianyang, China
    Hong Li, Mianyang Central Hospital, Mianyang, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.