Background <p>The number of frail older persons with hip fractures significantly increases. Some research indicated the incidence of mortality and adverse events for frail patients is higher than for non-frail patients. This article explores the incidence, development, and validation of a predictive model of serious adverse events and mortality in the 3-month following period.</p> Methods <p>This was an observational cohort study conducted at a tertiary hospital. Participants were consecutively admitted from December 2022 to August 2024. A total of 145 participants were included in this study. The LASSO regression and Cox proportional hazards regression analysis were developed to predict the model. Receiver operating characteristic (ROC) curves, Area under the curve (AUC), and C-index were used to assess model performance.</p> Results <p>26 (17.93%) patients have died or experienced serious adverse events after surgery in the 3-month follow up. The Cox proportional hazards regression analysis indicates age and the number of drugs for postoperative treatment are risk factors. Hemoglobin at admission and a high Barthel index of activities of daily living (before fracture two weeks) are protective factors. The model achieved a high AUC of 0.837 and a C-index of 0.772 (95% CI: 0.690–0.853). The sensitivity is 0.842 and the specificity is 0.675 which suggests great discrimination. The Hosmer-Lemeshow goodness-of-fit test shows <i>X</i><sup>2</sup> = 0.187 (<i>p</i> = 0.665) which indicates well-calibrated.</p> Conclusions <p>This study indicates a high incidence of death or serious adverse events within 3-month after surgery in frail older persons with hip fractures. Age, the number of drugs for postoperative treatment, hemoglobin at admission, and Barthel index of activities of daily living (before fracture two weeks) are predictors. The nomogram helps healthcare to screen patients with high risk and to provide references for perioperative management and discharge care.</p>

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Risk factors for death or serious adverse events within 3-month after surgery in frail older persons with hip fractures and development and validation of a risk prediction model: Based on LASSO-logistic regression

  • Yaqi Guan,
  • Lidan Zheng,
  • Yipei Wang,
  • Xiaoxiao Xu,
  • Yueying Zhu

摘要

Background

The number of frail older persons with hip fractures significantly increases. Some research indicated the incidence of mortality and adverse events for frail patients is higher than for non-frail patients. This article explores the incidence, development, and validation of a predictive model of serious adverse events and mortality in the 3-month following period.

Methods

This was an observational cohort study conducted at a tertiary hospital. Participants were consecutively admitted from December 2022 to August 2024. A total of 145 participants were included in this study. The LASSO regression and Cox proportional hazards regression analysis were developed to predict the model. Receiver operating characteristic (ROC) curves, Area under the curve (AUC), and C-index were used to assess model performance.

Results

26 (17.93%) patients have died or experienced serious adverse events after surgery in the 3-month follow up. The Cox proportional hazards regression analysis indicates age and the number of drugs for postoperative treatment are risk factors. Hemoglobin at admission and a high Barthel index of activities of daily living (before fracture two weeks) are protective factors. The model achieved a high AUC of 0.837 and a C-index of 0.772 (95% CI: 0.690–0.853). The sensitivity is 0.842 and the specificity is 0.675 which suggests great discrimination. The Hosmer-Lemeshow goodness-of-fit test shows X2 = 0.187 (p = 0.665) which indicates well-calibrated.

Conclusions

This study indicates a high incidence of death or serious adverse events within 3-month after surgery in frail older persons with hip fractures. Age, the number of drugs for postoperative treatment, hemoglobin at admission, and Barthel index of activities of daily living (before fracture two weeks) are predictors. The nomogram helps healthcare to screen patients with high risk and to provide references for perioperative management and discharge care.