ORIGINAL RESEARCH article
Front. Med.
Sec. Geriatric Medicine
Blood indicators for short-term mortality risk in older patients with hip fracture: association and predictive value
Provisionally accepted- People’s Hospital of Deyang City, Deyang, China
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Objectives: To investigate blood indicators associated with short-term mortality risk in older patients with hip fracture, and further evaluate the incremental predictive value of incorporating these indicators into existing clinical models. Methods: Data from 1881 patients in our institutional hip fracture database between January 2013 and December 2023 were retrospectively analyzed. The study outcome was all-cause mortality within 90 days of admission. Stepwise logistic regression, the Boruta algorithm, and Lasso regression were performed to identify features associated with mortality risk. Following feature selection, two predictive models were developed: Model A (clinical indicators only) and Model B (both clinical and blood indicators). Predictive performance was assessed using the area under the curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Results: Of the 1881 patients, 217 (11.5%) died within 90 days. Stepwise logistic regression identified 12 significant features associated with mortality risk, the Boruta algorithm identified 25 important features, and Lasso regression analysis selected 18 features with non-zero coefficients (all P < 0.05). Model B significantly outperformed Model A across all feature selection methods (all P < 0.001): stepwise logistic regression (AUC: 0.822 vs. 0.753), the Boruta algorithm (AUC: 0.820 vs. 0.749), and Lasso regression (AUC: 0.826 vs. 0.756). Model B also showed significant reclassification improvements (all P < 0.001): stepwise logistic regression (NRI: 0.733, IDI: 0.107), the Boruta algorithm (NRI: 0.762, IDI: 0.113), and Lasso regression (NRI: 0.725, IDI: 0.112). Conclusion: Various blood indicators were associated with 90-day mortality in older patients with hip fracture, and significantly enhanced the predictive ability of clinical models for short-term mortality risk. By utilizing these blood indicators, clinicians can comprehensively and objectively assess the physiological status of hip fracture patients at admission, thereby facilitating the early identification of high-risk patients and guiding personalized treatment strategies.
Keywords: Hip fracture, Mortality, Blood indicator, Predictive Value, Older adult
Received: 13 Aug 2025; Accepted: 12 Nov 2025.
Copyright: © 2025 Zhou, Zhang, Wu, Chen and Wang. 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: Zhicong Wang, wangzcong@hotmail.com
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.
