Objective to develop a user-friendly prediction tool of 1-year mortality for patients with hip fracture, in order to guide clinicians and patients on appropriate targeted preventive measures. Design population-based cohort study from 2011 to 2017 using nationwide data from the Danish Hip Fracture Registry. Subjects a total of 28,791 patients age 65 and above undergoing surgery for a first-time hip fracture. Methods patient-related prognostic factors at the time of admission were assessed as potential predictors: Nursing home residency, comorbidity (Charlson Comorbidity Index [CCI] Score), frailty (Hospital Frailty Risk Score), basic mobility (Cumulated Ambulation Score), atrial fibrillation, fracture type, body mass index (BMI), age and sex. Association with 1-year mortality examined by determining the cumulative incidence, applying univariable logistic regression and assessing discrimination (area under the receiver operating characteristics curve [AUROC]). The final model (logistic regression) was utilised on a development cohort (70% of patients). Discrimination and calibration were assessed on the validation cohort (remaining 30% of patients). Results all predictors showed an association with 1-year mortality, but discrimination was moderate. The final model included nursing home residency, CCI Score, Cumulated Ambulation Score, BMI and age. It had an acceptable discrimination (AUROC 0.74) and calibration, and predicted 1-year mortality risk spanning from 5 to 91% depending on the combination of predictors in the individual patient. Conclusions using information obtainable at the time of admission, 1-year mortality among patients with hip fracture can be predicted. We present a user-friendly chart for daily clinical practice and provide new insight regarding the interplay between prognostic factors.

中文翻译：

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髋部骨折患者死亡率预测模型的开发和验证

目的开发一种用户友好的髋部骨折患者1年死亡率预测工具，以指导临床医生和患者采取适当的有针对性的预防措施。使用丹麦髋部骨折登记处的全国数据设计 2011 年至 2017 年基于人群的队列研究。共有 28,791 名 65 岁及以上的患者因首次髋部骨折接受手术。方法 入院时与患者相关的预后因素被评估为潜在的预测因素：疗养院住院医师、合并症（查尔森合并症指数 [CCI] 评分）、虚弱（医院虚弱风险评分）、基本活动能力（累积步行评分）、心房颤动，骨折类型，体重指数（BMI），年龄和性别。通过确定累积发病率检查与 1 年死亡率的关联，应用单变量逻辑回归和评估歧视（接受者操作特征曲线下的面积 [AUROC]）。最终模型（逻辑回归）用于开发队列（70% 的患者）。在验证队列（剩余 30% 的患者）上评估了歧视和校准。结果所有预测因素均显示与 1 年死亡率相关，但歧视程度适中。最终模型包括疗养院住院医师、CCI 评分、累积步行评分、BMI 和年龄。它具有可接受的辨别力 (AUROC 0.74) 和校准，并预测 1 年死亡率风险范围为 5% 至 91%，具体取决于个体患者的预测因子组合。使用入院时可获得的信息得出结论，可以预测髋部骨折患者的 1 年死亡率。我们为日常临床实践提供了一个用户友好的图表，并就预后因素之间的相互作用提供了新的见解。