To analyze the risk factors associated with mortality within 1 year after surgery in elderly patients with hip fracture and to assess the value of the age-corrected Charlson comorbidity index in predicting this mortality risk

本研究旨在分析老年髋部骨折患者术后1年内死亡的相关危险因素,并评估年龄校正的Charlson合并症指数在预测该死亡风险方面的价值。

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Abstract

To investigate the determining risk factors for 1-year postoperative mortality in elderly patients with hip fracture and to assess the efficacy of the age-adjusted Charlson comorbidity index (ACCI) in predicting the risk of death. This study adopted a retrospective analysis method to focus on 652 elderly patients who underwent hip fracture surgery between January 2018 and November 2022 in our hospital. By systematically combing the patients' medical records, relevant data were collected and analyzed in depth for their association with morbidity and mortality rates within 1 year. In the 1-year follow-up for 652 elderly patients who underwent hip fracture surgery, the proportion of deaths due to disease amounted to 21.5% (140/652). Univariate analysis using the Cox proportional hazard model revealed that age, number of hospital days, ACCI, and the occurrence of postoperative pneumonia were significantly associated with the rate of morbidity and mortality within 1 year. Further multivariate Cox regression analysis confirmed that age (hazard ratio [HR], 1.087 [95% confidence interval [CI], 1.060-1.114]), ACCI (HR, 1.645 [95% CI, 1.548-1.747]), and postoperative pneumonia (HR, 2.353 [95% CI, 1.624-3.408]) served as independent risk factors that significantly influenced the patients' 1-year survival. The ACCI excelled in predicting the risk of 1-year postoperative mortality, with an AUC of 0.912 for its prediction model and a specificity and sensitivity of 0.834 and 0.871, respectively, when the threshold was set at 5.5. The results of this study emphasize that age, ACCI, and postoperative pneumonia are key risk factors affecting the survival of elderly patients with hip fracture at 1-year postoperatively. ACCI, as an effective predictive tool, can provide an important reference for the clinical assessment of patients' postoperative risk and help precision medical decision-making.

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