Guo Jiale, Shi Liuyang, Shi Kehai, Dai Ru, Wang Jian, Li Yehai
Department of Orthopedics, Chaohu Hospital of Anhui Medical University, Hefei, China.
Front Med (Lausanne). 2025 May 30;12:1500049. doi: 10.3389/fmed.2025.1500049. eCollection 2025.
Hip fractures are catastrophic events with a significant risk of mortality, making early identification of high-risk patients crucial. While previous studies have primarily focused on post-surgical mortality in hip fracture patients, less attention has been given to those who did not undergo surgery. This study aimed to develop a nomogram to predict 1-year mortality in older adults following hip fractures.
Patients hospitalized with hip fractures at a university hospital between May 2016 and December 2021 were included. Participants were randomly divided into training and validation cohorts (70:30 ratio). After selecting key variables, the nomogram was constructed, and its performance was evaluated in both cohorts.
A total of 619 patients were included, with 136 (21.97%) experiencing mortality within one year. LASSO regression was used to account for multicollinearity, selecting variables such as age, coronary heart disease, surgery, hemoglobin, aspartate transaminase, and blood urea nitrogen. The nomogram achieved AUCs of 0.83 (95% CI: 0.78-0.88) and 0.81 (95% CI: 0.73-0.89) in the training and validation cohorts, respectively, demonstrating excellent calibration and clinical utility.
The nomogram effectively predict 1-year mortality risk in older adults following hip fractures.
髋部骨折是灾难性事件，具有很高的死亡风险，因此早期识别高危患者至关重要。虽然先前的研究主要关注髋部骨折患者的术后死亡率，但对未接受手术的患者关注较少。本研究旨在开发一种列线图，以预测老年髋部骨折患者的1年死亡率。
纳入2016年5月至2021年12月在一家大学医院因髋部骨折住院的患者。参与者被随机分为训练队列和验证队列（比例为70:30）。在选择关键变量后，构建列线图，并在两个队列中评估其性能。
共纳入619例患者，其中136例（21.97%）在一年内死亡。采用LASSO回归处理多重共线性，选择年龄、冠心病、手术、血红蛋白、天冬氨酸转氨酶和血尿素氮等变量。列线图在训练队列和验证队列中的AUC分别为0.83（95%CI：0.78-0.88）和0.81（95%CI：0.73-0.89），显示出良好的校准和临床实用性。
该列线图可有效预测老年髋部骨折患者的1年死亡风险。
