A New Nomogram Model for Predicting 1-Year All-Cause Mortality After Hip Arthroplasty in Nonagenarians With Hip Fractures: A 20-Year Period Retrospective Cohort Study.

Background: China has become an ageing society and as it continues to age, it will face an increasing number of hip fractures in nonagenarians. However, few preoperative assessment tools to determine the postoperative mortality risk in nonagenarians with hip fracture were available. The aim of this study was to identify all-cause mortality risk factors after hip arthroplasty in nonagenarians with hip fractures and to establish a new nomogram model to optimize the individualized hip arthroplasty in nonagenarians with hip fractures.

Methods: We retrospectively studied 246 consecutive nonagenarians diagnosed with hip fracture from August 2002 to February 2021 at our center. During the follow-up, 203 nonagenarians with a median age of 91.9 years treated with hip arthroplasty were included, of which 136 were females and 67 were males, and 43 nonagenarians were excluded (40 underwent internal fixation and 3 were lost to follow-up). The full cohort was randomly divided into training (50%) and validation (50%) sets. The potential predictive factors for 1-year all-cause mortality after hip arthroplasty were assessed by univariate and multivariate COX proportional hazards regression on the training set, and then, a new nomogram model was established and evaluated by concordance index (C-index) and calibration curves.

Results: After analyzing 44 perioperative variables including demographic characteristics, vital signs, surgical data, laboratory tests, we identified that age-adjusted Charlson Comorbidity Index (aCCI) (= 0.042), American Society of Anesthesiologists (ASA) classification (= 0.007), Urea (= 0.028), serum Ca (= 0.011), postoperative hemoglobin (= 0.024) were significant predictors for 1-year all-cause mortality after hip arthroplasty in the training set. The nomogram showed a robust discrimination, with a C-index of 0.71 (95%CIs, 0.68-0.78). The calibration curves for 1-year all-cause mortality showed optimal agreement between the probability as predicted by the nomogram and the actual probability in training and validation sets.

Conclusion: A novel nomogram model integrating 5 independent predictive variables were established and validated. It can effectively predict 1-year all-cause mortality after hip arthroplasty in nonagenarians with hip fracture and lead to a more optimized and rational therapeutic choice.