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A risk calculator for short-term morbidity and mortality after hip fracture surgery
Andrew J Pugely1, Christopher T Martin, Yubo Gao
1*Department of Orthopaedic Surgery and Rehabilitation, University of Iowa Hospitals and Clinics, Iowa City, IA; and †Division of Biomechanics, Department of Orthopaedic Surgery and Rehabilitation, University of Iowa, Iowa City, IA.
Objective:
Hip fractures are a common source of morbidity and mortality among the elderly. Although multiple prior studies have identified risk factors for poor outcomes, few studies have presented a validated risk stratification calculator.
Methods:
The American College of Surgeons National Surgical Quality Improvement Program database was used to identify 4331 patients undergoing surgery for hip fracture between 2005 and 2010. Patient demographics, comorbidities, laboratory values, and operative characteristics were compared in a univariate analysis, and a multivariate logistic regression analysis was then used to identify independent predictors of 30-day morbidity and mortality. Weighted values were assigned to each independent risk factor and used to create predictive models of 30-day morbidity, minor complication risk, major complication risk, and total complication risk. The models were internally validated with randomly partitioned 80%/20% cohort groups.
Results:
Thirty-day mortality was 5.9% and morbidity was 30.0%. Patient age, especially age greater than 80 years [mortality: odds ratio (OR): 2.41, 95% confidence interval (CI): 1.17-4.99); morbidity: OR: 1.43, 95% CI: 1.05-1.94], and male gender (mortality: OR: 2.28, 95% CI: 1.61-3.22; morbidity: OR: 1.26, 95% CI: 1.03-1.54) were associated with both increased mortality and morbidity. An increased American Society of Anesthesia class had the highest negative impact on total complication incidence in the scoring models. Additionally, complete functional dependence, active malignancy, patient race, cardiopulmonary disease, laboratory derangements, prolonged operating time, and open versus percutaneous surgery independently influenced outcomes. Risk scores, based on weighted models, which included the aforementioned variables, predicted mortality (P < 0.001, C index: 0.702) and morbidity (P < 0.001, C index: 0.670) after hip fracture surgery.
Conclusions:
In this study, we have developed an internally validated method for risk stratifying patients undergoing hip fracture surgery, and this model is predictive of both 30-day morbidity and mortality. Our model could be useful for identifying high-risk individuals, for obtaining informed consent, and for risk-adjusted comparisons of outcomes between institutions.
Level Of Evidence:
Prognostic level II. See instructions for authors for a complete description of levels of evidence.