Ding Jie, Sun Guoli, Ren Yifei, Xu Jiajia, Hu Qingqing, Luo Jun, Wu Zhaowen, Chu Ting
School of Nursing, Zhejiang Chinese Medical University, Hangzhou, Zhejiang Province, 310053, People's Republic of China.
Department of Orthopaedics, The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang Province, 310053, People's Republic of China.
Ther Clin Risk Manag. 2025 Jul 10;21:1047-1058. doi: 10.2147/TCRM.S523040. eCollection 2025.
Adverse outcomes after hip arthroplasty in elderly patients are frequently observed; however, most existing studies concentrate on single complications. Comprehensive predictive models for a wider range of adverse outcomes remain insufficient. This study explores this issue and proposes new approaches for clinical practice.
This study aimed to construct and verify risk prediction model for adverse outcomes after hip arthroplasty in elderly patients.
The TRIPOD checklist was followed to guide the reporting of this study. Data from 620 subjects who underwent hip arthroplasty at a tertiary A-level hospital from January 1, 2021 to December 31, 2023 were used for the modelling group. Additionally, 264 post-hip arthroplasty patients admitted to the orthopaedic department of another tertiary A-level hospital from January 1, 2024 to December 31, 2024 were selected as the validation group. Risk prediction models were constructed by logistic regression, plotted in column line graphs and evaluated for their predictive effectiveness.
The factors included in the prediction model were age, malignancy history, surgical procedure, albumin, prothrombin time, ASA grade, operation duration, and changeover surgery status. Hosmer-Lemeshow test, =5.418, =0.712, the area under the receiver operating characteristic curve (AUC) was 0.902. The Youden index is 0.668, with a sensitivity of 0.84 and a specificity of 0.828. The correct practical application rate was 83.33%.
The risk prediction model constructed in this study demonstrates favourable predictive performance and can serve as a reference for healthcare professionals in predicting the risk of adverse outcomes after hip arthroplasty in elderly patients.
老年患者髋关节置换术后不良结局屡见不鲜；然而，大多数现有研究集中于单一并发症。针对更广泛不良结局的综合预测模型仍显不足。本研究探讨此问题并提出临床实践新方法。
本研究旨在构建并验证老年患者髋关节置换术后不良结局的风险预测模型。
遵循TRIPOD清单指导本研究报告。将2021年1月1日至2023年12月31日在一家三级甲等医院接受髋关节置换术的620例患者的数据用于建模组。此外，选取2024年1月1日至2024年12月31日在另一家三级甲等医院骨科住院的264例髋关节置换术后患者作为验证组。通过逻辑回归构建风险预测模型，绘制列线图并评估其预测效能。
预测模型纳入的因素有年龄、恶性肿瘤病史、手术方式、白蛋白、凝血酶原时间、美国麻醉医师协会（ASA）分级、手术时长及转换手术状态。Hosmer-Lemeshow检验，χ² = 5.418，P = 0.712，受试者工作特征曲线（AUC）下面积为0.902。约登指数为0.668，灵敏度为0.84，特异度为0.828。正确实际应用率为83.33%。
本研究构建的风险预测模型显示出良好的预测性能，可为医疗保健专业人员预测老年患者髋关节置换术后不良结局风险提供参考。
