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ORIGINAL RESEARCH article

Front. Public Health
Sec. Aging and Public Health
Volume 12 - 2024 | doi: 10.3389/fpubh.2024.1526660

Construction and Validation of a Prediction Model for Fall Risk in hospitalized Older Adults with Osteoporosis

Provisionally accepted
Li Sun Li Sun Hai-Yan Gu Hai-Yan Gu Guan-Hua Xu Guan-Hua Xu Jia-Wei Jiang Jia-Wei Jiang Ting-Ting Wang Ting-Ting Wang Dan-Dan Li Dan-Dan Li Bai-hong Cui Bai-hong Cui *
  • Second Affiliated Hospital of Nantong University, Nantong, Jiangsu Province, China

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

    The aim of this study is to develop and validate a prediction model for fall risk factors in hospitalized older adults with osteoporosis.: A total of 615 older adults with osteoporosis hospitalized at a tertiary (grade 3A) hospital in Nantong City, Jiangsu Province, China, between September 2022 and August 2023 were selected for the study using convenience sampling. Fall risk factors were identified using univariate and logistic regression analyses, and a predictive risk model was constructed and visualized through a nomogram. Model performance was evaluated using the area under the receiver operator characteristic curve (AUC), Hosmer-Lemeshow goodness-of-fit test, and clinical decision curve analysis, assessing the discrimination ability, calibration, and clinical utility of the model. Results: Based on logistic regression analysis, we identified several significant fall risk factors for older adults with osteoporosis: gender of the study participant, bone mineral density, serum calcium levels, history of falls, fear of falling, use of walking aids, and impaired balance. The AUC was 0.798 (95% CI: 0.763-0.830), with a sensitivity of 80.6%, a specificity of 67.9%, a maximum Youden index of 0.485, and a critical threshold of 121.97 points. The Hosmer-Lemeshow test yielded a χ 2 value of 8.147 and P = 0.419, indicating good model calibration. Internal validation showed a C-index of 0.799 (95% CI: 0.768-0.801), indicating the model's high discrimination ability. Calibration curves showed good agreement between predicted and observed values, confirming good calibration. The clinical decision curve analysis further supported the model's clinical utility. Conclusion The prediction model constructed and verified in this study was to predict fall risk for hospitalized older adults with osteoporosis, providing a valuable tool for clinicians to implement targeted interventions for patients with high fall risks.

    Keywords: fall, nomogram, Nursing, Osteoporosis (OP), Prediction model, Risk factors

    Received: 12 Nov 2024; Accepted: 30 Dec 2024.

    Copyright: © 2024 Sun, Gu, Xu, Jiang, Wang, Li and Cui. 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: Bai-hong Cui, Second Affiliated Hospital of Nantong University, Nantong, 226000, Jiangsu Province, 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.