Literature DB >> 23872716

A risk calculator for short-term morbidity and mortality after hip fracture surgery.

Andrew J Pugely1, Christopher T Martin, Yubo Gao, Noelle F Klocke, John J Callaghan, J Lawrence Marsh.   

Abstract

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.

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Year:  2014        PMID: 23872716     DOI: 10.1097/BOT.0b013e3182a22744

Source DB:  PubMed          Journal:  J Orthop Trauma        ISSN: 0890-5339            Impact factor:   2.512


  38 in total

1.  Prophylactic Fixation Can Be Cost-effective in Preventing a Contralateral Bisphosphonate-associated Femur Fracture.

Authors:  Sam Y Jiang; David J Kaufman; Bonnie Y Chien; Michael Longoria; Ross Shachter; Julius A Bishop
Journal:  Clin Orthop Relat Res       Date:  2019-03       Impact factor: 4.176

2.  Prognostic Factors Predicting Early Recovery of Pre-fracture Functional Mobility in Elderly Patients With Hip Fracture.

Authors:  Daegu Lee; Jae Yong Jo; Ji Sun Jung; Sang Jun Kim
Journal:  Ann Rehabil Med       Date:  2014-12-24

3.  CORR Insights®: Diabetes confers little to no increased risk of postoperative complications after hip fracture surgery in geriatric patients.

Authors:  Andrew J Pugely
Journal:  Clin Orthop Relat Res       Date:  2014-10-10       Impact factor: 4.176

4.  Combination of red cell distribution width and American Society of Anesthesiologists score for hip fracture mortality prediction.

Authors:  P Yin; H Lv; L Zhang; A Long; L Zhang; P Tang
Journal:  Osteoporos Int       Date:  2016-03-14       Impact factor: 4.507

5.  Results of Database Studies in Spine Surgery Can Be Influenced by Missing Data.

Authors:  Bryce A Basques; Ryan P McLynn; Michael P Fice; Andre M Samuel; Adam M Lukasiewicz; Daniel D Bohl; Junyoung Ahn; Kern Singh; Jonathan N Grauer
Journal:  Clin Orthop Relat Res       Date:  2017-12       Impact factor: 4.176

Review 6.  Hip fracture registries: utility, description, and comparison.

Authors:  P Sáez-López; F Brañas; N Sánchez-Hernández; N Alonso-García; J I González-Montalvo
Journal:  Osteoporos Int       Date:  2016-11-21       Impact factor: 4.507

7.  Nationwide Inpatient Sample and National Surgical Quality Improvement Program give different results in hip fracture studies.

Authors:  Daniel D Bohl; Bryce A Basques; Nicholas S Golinvaux; Michael R Baumgaertner; Jonathan N Grauer
Journal:  Clin Orthop Relat Res       Date:  2014-03-11       Impact factor: 4.176

8.  Standardized practice is associated with low rate of surgical site infection in orthopaedic trauma.

Authors:  Daniel Schmitt; Megan Rodts; Benjamin Davis; Hobie Summers; Mitchell Bernstein; William Lack
Journal:  J Clin Orthop Trauma       Date:  2018-12-30

9.  Incidence And Risk Factors For 30-Day Readmissions After Hip Fracture Surgery.

Authors:  Christopher T Martin; Yubo Gao; Andrew J Pugely
Journal:  Iowa Orthop J       Date:  2016

10.  The effect of resident participation on short-term outcomes after orthopaedic surgery.

Authors:  Andrew J Pugely; Yubo Gao; Christopher T Martin; John J Callagh; Stuart L Weinstein; J Lawrence Marsh
Journal:  Clin Orthop Relat Res       Date:  2014-07       Impact factor: 4.176

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