Predicting 1-year all-cause mortality after hip arthroplasty for hip fracture: A retrospective cohort study and nomogram development

This retrospective cohort study aimed to identify risk factors for 1-year all-cause mortality after hip arthroplasty for hip fracture and to develop and validate a predictive model. Clinical data of patients admitted between January 2020 and December 2023 were retrospectively collected. Independent risk factors were identified using logistic regression, and a nomogram was constructed. Model performance was evaluated by receiver operating characteristic analysis, Hosmer-Lemeshow test, calibration curve, and decision curve analysis, with internal validation by bootstrap and cross-validation. Among 876 patients, 161 (18.4%) died within 1 year after surgery. Five independent risk factors were identified: age > 75 years, BMI ≤ 20 kg/m2, stroke, chronic lung disease, and deep vein thrombosis. The model showed good discrimination with AUC values of 0.867 (training set) and 0.805 (validation set), and demonstrated good calibration and clinical utility. Older age, low BMI, stroke, chronic lung disease, and deep vein thrombosis were associated with increased mortality risk. The nomogram provides a practical tool for perioperative risk assessment and may guide targeted interventions to improve survival in hip fracture patients.

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Journal
Medicine
Published
2026-01-09
DOI
https://doi.org/10.1097/md.0000000000045767
Primary Topic
Hip and Femur Fractures
Type
article
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article

Predicting 1-year all-cause mortality after hip arthroplasty for hip fracture: A retrospective cohort study and nomogram development

Chao Hu, Qing Xiao
Medicine
Hip and Femur Fractures
article

Predicting 1-year all-cause mortality after hip arthroplasty for hip fracture: A retrospective cohort study and nomogram development

Chao Hu, Qing Xiao
article en

Abstract

This retrospective cohort study aimed to identify risk factors for 1-year all-cause mortality after hip arthroplasty for hip fracture and to develop and validate a predictive model. Clinical data of patients admitted between January 2020 and December 2023 were retrospectively collected. Independent risk factors were identified using logistic regression, and a nomogram was constructed. Model performance was evaluated by receiver operating characteristic analysis, Hosmer-Lemeshow test, calibration curve, and decision curve analysis, with internal validation by bootstrap and cross-validation. Among 876 patients, 161 (18.4%) died within 1 year after surgery. Five independent risk factors were identified: age > 75 years, BMI ≤ 20 kg/m2, stroke, chronic lung disease, and deep vein thrombosis. The model showed good discrimination with AUC values of 0.867 (training set) and 0.805 (validation set), and demonstrated good calibration and clinical utility. Older age, low BMI, stroke, chronic lung disease, and deep vein thrombosis were associated with increased mortality risk. The nomogram provides a practical tool for perioperative risk assessment and may guide targeted interventions to improve survival in hip fracture patients.

MedicineVol. 105(2)
Suizhou Central Hospital (CN)
Openalex Percentile: Top 92%
Hip and Femur Fractures
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