ArticlePakistan journal of medical sciences2024
Risk factors and nomogram predictive model of severe postoperative complications in elderly patients with intertrochanteric fractures.
Article in Pakistan journal of medical sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- All-Cause Mortality Risk in Elderly Patients with Femoral Neck and Intertrochanteric Fractures: A Predictive Model Based on Machine Learning.Clinical interventions in aging · 2025Article
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2 authors.
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Abstract
Objective: To analyze risk factors of severe postoperative complications in elderly patients with intertrochanteric fractures (ITF), and to construct a predictive model. Methods: The medical records of 316 elderly patients with ITF who underwent surgical treatment in Suzhou Hospital of Integrated Traditional Chinese and Western Medicine from January 2020 to December 2022 were retrospectively analyzed. Univariate and multivariate logistic regression analyses were performed to identify risk factors of severe postoperative complications. A nomogram prediction model was constructed using the RMS package of R4.1.2 software. Accuracy and stability of the model was assessed using the receiver operating characteristic (ROC) curve, Hosmer-Lemeshow goodness-of-fit test, and decision curve analysis. Results: Age, American Society of Anesthesiologists (ASA) grading, combined medical diseases, preoperative bedridden condition, frailty, and preoperative albumin levels were all risk factors for severe postoperative complications in ITF patients were noted. These factors were then used to build a risk prediction model that had an area under the ROC curve (AUC) of 0.899 (95% confidence interval ( Conclusions: Age, ASA grading, combined medical diseases, preoperative bedridden condition, frailty, and preoperative albumin levels were independent risk factors for severe postoperative complications in elderly ITF patients. The constructed prediction model based on the above risk factors has a high predictive value.
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