ArticleFrontiers in physiology2025
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.
Article in Frontiers in physiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Factors influencing high expectations in patients undergoing corneal transplantation.Scientific reports · 2026Article
- Shift in Patient Demographics of Open Thoracoabdominal Aortic Aneurysm Repair Patients in the Endovascular Era.Journal of clinical medicine · 2025Article
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6 authors.
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Abstract
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. Results: 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, χ Conclusion: 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.
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