Qi Ruilong, Xu Guohong, Lin Zhengtong, Wang Li-Hong
Department of Orthopedics, Affiliated Dongyang Hospital of Wenzhou Medical University, Dongyang, Zhejiang, China.
J Bone Miner Metab. 2025 Jul 18. doi: 10.1007/s00774-025-01616-9.
Hip fracture (HF) is one of the leading causes of mortality and disability in older populations. Hip refracture (HRF) is more serious than HF. We examined the survival rates of patients with HRFs at the Affiliated Dongyang Hospital of Wenzhou Medical University and developed a prediction model for their survival outcomes.
This study involved identifying and analyzing patients with HRFs from January 2013 to August 2023. Utilizing our hospital's database, we systematically extracted these patients' information. We monitored the survival time and constructed Kaplan-Meier (K-M) survival curve. Through Cox proportional hazards regression analyses, independent risk factors were identified. Based on these factors, a survival prediction model was developed and its reliability was evaluated by the receiver operating characteristic (ROC) curve. In addition, patients who refused surgery were excluded, the eligible patients were divided into a long waiting group (> 48 h) and a short waiting group (≤ 48 h). According to a similar process, independent risk factors were identified. Another nomogram chart and ROC curve were conducted.
Data from 174 patients were used, presenting a median survival time of 40 months. Both univariate and multivariate analyses identified age (HR = 1.71, 95% CI: 1.26-2.32), surgical intervention (HR = 0.34, 95% CI: 0.21-0.55), number of comorbidities (HR = 1.44, 95% CI: 1.09-1.92) and lymphocyte levels (HR = 0.75, 95% CI: 0.61-0.92) as independent influence factors. Based on these factors, a nomogram chart was constructed. The areas under the ROC curve for predicting 1-year, 2-year, and 3-year survival rates were 0.748, 0.794 and 0.806 respectively. Additionally, through regression analysis of surgical patients, some factors (age, number of comorbidities and lymphocyte levels) were supported as independent influence factors.
Advanced age, non-surgical management, multiple comorbidities and lower lymphocyte levels showed a higher risk of all-cause mortality among the patients with HRFs, and these factors were associated with a poor prognosis in this patient population. This study may be useful for improving these patients' prognosis.
髋部骨折（HF）是老年人群死亡和残疾的主要原因之一。髋部再骨折（HRF）比髋部骨折更为严重。我们研究了温州医科大学附属东阳医院HRF患者的生存率，并建立了其生存结局的预测模型。
本研究涉及识别和分析2013年1月至2023年8月期间的HRF患者。利用我院数据库，系统提取这些患者的信息。我们监测生存时间并构建Kaplan-Meier（K-M）生存曲线。通过Cox比例风险回归分析，确定独立危险因素。基于这些因素，建立生存预测模型，并通过受试者工作特征（ROC）曲线评估其可靠性。此外，排除拒绝手术的患者，将符合条件的患者分为长等待组（>48小时）和短等待组（≤48小时）。按照类似流程，确定独立危险因素。绘制另一个列线图和ROC曲线。
使用了174例患者的数据，中位生存时间为40个月。单因素和多因素分析均确定年龄（HR = 1.71，95%CI：1.26 - 2.32）、手术干预（HR = 0.34，95%CI：0.21 - 0.55）、合并症数量（HR = 1.44，95%CI：1.09 - 1.92）和淋巴细胞水平（HR = 0.75，95%CI：0.61 - 0.92）为独立影响因素。基于这些因素，绘制了列线图。预测1年、2年和3年生存率的ROC曲线下面积分别为0.748、0.794和0.806。此外，通过对手术患者的回归分析，一些因素（年龄、合并症数量和淋巴细胞水平）被确认为独立影响因素。
高龄、非手术治疗管理、多种合并症以及较低的淋巴细胞水平在HRF患者中显示出全因死亡风险较高，并且这些因素与该患者群体的预后不良相关。本研究可能有助于改善这些患者的预后。
