ORIGINAL RESEARCH article
Front. Physiol.
Sec. Computational Physiology and Medicine
Volume 16 - 2025 | doi: 10.3389/fphys.2025.1628450
Development and Validation of a Risk Prediction Model for Perioperative Acute Kidney Injury in Non-Cardiac and Non-Urological Surgery Patients: A Retrospective Cohort Study
Provisionally accepted
- 1Henan Provincial People's Hospital, Zhengzhou, China
- 2Xinxiang Medical University, Xinxiang, China
- 3Zhengzhou University, Zhengzhou, China
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Background: This study presents a predictive model designed to fill the gap in tools for predicting perioperative acute kidney injury (AKI) in patients undergoing non-cardiac, non-urological surgeries, with the goal of improving clinical decision-making and patient outcomes.Methods: A retrospective cohort of 40,520 patients aged 65 and older who underwent non-cardiac, non-urological surgeries was analyzed. Key risk factors were identified using univariable logistic regression and LASSO, while multivariate logistic regression was applied to develop and validate the model.The prediction model, based on 18 key variables including demographic data, comorbidities, and intraoperative factors, demonstrated strong discriminatory power for predicting perioperative AKI (AUC = 0.803; 95% CI, 0.783-0.823). It also showed a good fit in the validation cohort (Hosmer-Lemeshow test, χ² = 5.895, P = 0.750). Decision curve analysis further confirmed the model's significant clinical utility.This model effectively predicts perioperative AKI, providing a valuable tool for personalized risk assessment and prevention strategies in non-cardiac, non-urological surgeries.Further validation in diverse populations is recommended to optimize its clinical application.
Keywords: Prediction model, Risk Assessment, Perioperative acute kidney injury (AKI), Non-cardiac, nonurological surgeries, clinical decision-making
Received: 14 May 2025; Accepted: 08 Jul 2025.
Copyright: © 2025 Cong, Zou, Zhu, Li, Liu and Zhang. 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: Jiaqiang Zhang, Henan Provincial People's Hospital, Zhengzhou, China
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