Background Hip fractures in older people result in increased mortality. Objective We developed and validated an accurate and simple prognostic scoring system for hip fractures that can be used preoperatively. Design Retrospective study. Setting Multicenter. Participants Patients aged ≥65 years with hip fractures who underwent surgery between 2011 and 2021 were enrolled. Methods The significant factors were determined with logistic regression analysis, and a scoring system was developed. The patients were classified into three groups, and a log-rank test was performed to evaluate 1-year survival rates. The model was internally and externally validated using the 5-fold cross-validation and data from another hospital, respectively. Results We included 1026 patients. The analysis revealed eight significant prognostic factors: sex, body mass index, history of chronic heart failure and malignancy, activities of daily living (ADLs) before injury, hemoglobin and the prognostic nutritional index (PNI) at injury, and the American Society of Anesthesiologists Physical Status. The area under the receiver operating characteristic curve (AUC) after internal validation was 0.853. The external validation data consisted of 110 patients. The AUC of the model for the validation data was 0.905, showing outstanding discrimination. Sensitivity and specificity were 88.7% vs. 100% and 93.3% vs. 95.2% for the development and validation data, respectively. Conclusions We developed and validated an accurate and simple prognostic scoring system for hip fractures using only preoperative factors. Our findings highlight PNI as an important predictor of prognosis in hip fracture patients.

中文翻译：

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老年髋部骨折患者 1 年死亡率预后评分系统的开发和验证


背景 老年人髋部骨折导致死亡率增加。目的 我们开发并验证了一种准确、简单的髋部骨折预后评分系统，可在术前使用。设计 回顾性研究。设置 Multicenter。参与者 2011 年至 2021 年间接受手术的 ≥65 岁髋部骨折患者被纳入。方法 采用 logistic 回归分析确定显著因素，并建立评分系统。将患者分为 3 组，进行对数秩检验以评估 1 年生存率。该模型分别使用 5 倍交叉验证和来自另一家医院的数据进行了内部和外部验证。结果 我们纳入了 1026 例患者。分析揭示了八个重要的预后因素：性别、体重指数、慢性心力衰竭和恶性肿瘤病史、受伤前的日常生活活动 （ADL）、受伤时的血红蛋白和预后营养指数 （PNI），以及美国麻醉医师协会的身体状况。内部验证后受试者工作特征曲线下面积 （AUC） 为 0.853。外部验证数据由 110 名患者组成。验证数据的模型 AUC 为 0.905，显示出出色的辨别力。开发和验证数据的敏感性和特异性分别为 88.7% vs. 100% 和 93.3% vs. 95.2%。结论 我们仅使用术前因素开发并验证了准确、简单的髋部骨折预后评分系统。我们的研究结果强调 PNI 是髋部骨折患者预后的重要预测因子。