ArticleThe Journal of clinical endocrinology and metabolism2025
Secular Trends in Hip Fracture Mortality and Predictors of Mortality From the NSQIP Database.
Article in The Journal of clinical endocrinology and metabolism, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Association between preoperative fear of falling and mortality after hip fracture surgery in older adults: a post-hoc analysis of a prospective cohort.European geriatric medicine · 2026Article
- Are machine learning models superior to logistic regression models to predict 30-day mortality post-hip fracture surgery?JBMR plus · 2026Article
- Association of serum high creatinine-to-albumin ratio with increased 1-year mortality in older patients following hip fracture surgery.Frontiers in medicine · 2026Article
- Secular Trends in Hip Fracture Mortality and Predictors of Mortality From the NSQIP Database.The Journal of clinical endocrinology and metabolism · 2025Article
- Parsimonious and explainable machine learning for predicting mortality in patients post hip fracture surgery.Scientific reports · 2025Article
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Authors and funding
7 authors.
Funding
Abstract
contextHip fractures incur high morbidity and mortality. Data on secular trends in mortality from hip fractures and risk predictive models are scarce.
objectiveWe aim to describe secular trends in 30-day mortality after hip fracture surgery from the 2011-2017 National Surgical Quality Improvement Program database, identify preoperative and on-discharge predictors of 30-day mortality, and develop risk calculators.
methodsWe calculated yearly proportions of deaths and examined survival using Kaplan-Meier curves. We implemented logistic regressions models, using SPSS and created calculators using Excel.
resultsIn 84 824 cases of hip fracture surgery, the overall 30-day mortality was 6.8%. It decreased from 8.1% to 6.5% between 2011 and 2017 (P < .001). Significant preoperative predictors of 30-day mortality on admission were male gender, age, lower body mass index, White race, poorer functional health status, higher creatinine, lower hematocrit, >10% weight loss in the past 6 months, congestive heart failure within 30 days before surgery, and chronic obstructive pulmonary disease. Predictors on discharge included preoperative predictors with the exception of White race, hematocrit, and >10% weight loss in the past 6 months, and the addition of unplanned intubation, cerebrovascular accident, myocardial infarction, and pneumonia. The parsimonious preoperative risk calculator for mortality had 10 variables, an area under the curve (AUC) of 0.739, and a model fit R2 of 0.9716. The on-discharge calculator had 11 variables, an AUC of 0.800, and an R2 of 0.9924.
conclusionThirty-day mortality after hip fracture surgery decreased significantly from 2011 to 2017. Readily available clinical risk factors predict mortality preoperatively and on discharge. While most predictors are nonmodifiable, the calculators may better inform clinical decision-making.
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