Risk factors and nomogram predictive model of severe postoperative complications in elderly patients with intertrochanteric fractures.

IF 1.2 4区 医学 Q2 MEDICINE, GENERAL & INTERNAL
Ping Xu, Yanqiu Xu
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引用次数: 0

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 (CI): 0.846-0.951). The internal validation results of the Bootstrap method showed that the C-index value of the model was 0.899, and the calibration curve had a good fit with the ideal curve.

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.

转子间骨折老年患者术后严重并发症的风险因素和提名图预测模型。
目的分析转子间骨折(ITF)老年患者术后严重并发症的风险因素,并构建预测模型:回顾性分析2020年1月至2022年12月期间在苏州市中西医结合医院接受手术治疗的316例老年转子间骨折患者的病历。进行单变量和多变量逻辑回归分析,以确定术后严重并发症的风险因素。使用R4.1.2软件的RMS包构建了一个提名图预测模型。使用接收者操作特征曲线(ROC)、Hosmer-Lemeshow拟合度检验和决策曲线分析评估了模型的准确性和稳定性:结果:年龄、美国麻醉医师协会(ASA)分级、合并内科疾病、术前卧床情况、虚弱程度和术前白蛋白水平都是导致 ITF 患者术后严重并发症的风险因素。然后利用这些因素建立了一个风险预测模型,其 ROC 曲线下面积 (AUC) 为 0.899(95% 置信区间 (CI):0.846-0.951)。Bootstrap法的内部验证结果显示,该模型的C指数值为0.899,校准曲线与理想曲线拟合良好:结论:年龄、ASA分级、合并内科疾病、术前卧床情况、体弱和术前白蛋白水平是老年ITF患者术后严重并发症的独立危险因素。根据上述风险因素构建的预测模型具有很高的预测价值。
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来源期刊
Pakistan Journal of Medical Sciences
Pakistan Journal of Medical Sciences 医学-医学:内科
CiteScore
4.10
自引率
9.10%
发文量
363
审稿时长
3-6 weeks
期刊介绍: It is a peer reviewed medical journal published regularly since 1984. It was previously known as quarterly "SPECIALIST" till December 31st 1999. It publishes original research articles, review articles, current practices, short communications & case reports. It attracts manuscripts not only from within Pakistan but also from over fifty countries from abroad. Copies of PJMS are sent to all the import medical libraries all over Pakistan and overseas particularly in South East Asia and Asia Pacific besides WHO EMRO Region countries. Eminent members of the medical profession at home and abroad regularly contribute their write-ups, manuscripts in our publications. We pursue an independent editorial policy, which allows an opportunity to the healthcare professionals to express their views without any fear or favour. That is why many opinion makers among the medical and pharmaceutical profession use this publication to communicate their viewpoint.
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