Eric Wei Liang Cher1, John Carson Allen2, Tet Sen Howe3, Joyce Suang Bee Koh3. 1. Department of Orthopaedic Surgery, Singapore General Hospital, Singapore, Singapore. ericcher@gmail.com. 2. Centre of Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore. 3. Department of Orthopaedic Surgery, Singapore General Hospital, Singapore, Singapore.
Abstract
The aim of this study was to investigate the association of surgical delay and comorbidities with the risk of mortality after hip fracture surgeries. We found that CCI was the dominant factor in predicting both short- and long-term mortality, and its effect is vital in the prognostication of survivorship. INTRODUCTION: Hip fracture is a growing concern and a delay in surgery is often associated with a poorer outcome. We hypothesized that a higher Charlson Comorbidity Index (CCI) portends greater risk of mortality than a delay in surgery. Our aim was to investigate the associations of surgical delay and CCI with risk of mortality and to determine the dominant predictor. METHODS: This retrospective study examines hip fracture data from a large tertiary hospital in Singapore over the period January 2013 through December 2015. Data collected included age, gender, CCI, delay of surgery, fracture patterns, and the American Society of Anaesthesiologist (ASA) score. Post-operative outcomes analyzed included mortality at inpatient, at 30 and 90 days, and at 2 years. RESULTS: A total of 1004 patients with hip fractures were included in this study. Study mortality rates were 1.1% (n = 11) during in-hospital admission, 1.8% (n = 18) at 30 days, 2.7% (n = 27) at 90 days, and 13.3% (n = 129) at 2 years. Lost to follow-up rate at 2 years was 3.3%. We found that CCI was consistently the dominant factor in predicting both short- and long-term mortality. A CCI score of 5 was identified as the inflection point above which comorbidity at baseline presented a greater risk of mortality than a delay in surgery. CONCLUSION: Our analysis showed that CCI is the dominant predictor of both short- and long-term mortality compared with delay in surgery. The effect of CCI is vital in the prognostication of mortality in patients surgically treated for hip fractures.
The aim of this study was to investigate the association of surgical delay and comorbidities with the risk of mortality after hip fracture surgeries. We found that CCI was the dominant factor in predicting both short- and long-term mortality, and its effect is vital in the prognostication of survivorship. INTRODUCTION: Hip fracture is a growing concern and a delay in surgery is often associated with a poorer outcome. We hypothesized that a higher Charlson Comorbidity Index (CCI) portends greater risk of mortality than a delay in surgery. Our aim was to investigate the associations of surgical delay and CCI with risk of mortality and to determine the dominant predictor. METHODS: This retrospective study examines hip fracture data from a large tertiary hospital in Singapore over the period January 2013 through December 2015. Data collected included age, gender, CCI, delay of surgery, fracture patterns, and the American Society of Anaesthesiologist (ASA) score. Post-operative outcomes analyzed included mortality at inpatient, at 30 and 90 days, and at 2 years. RESULTS: A total of 1004 patients with hip fractures were included in this study. Study mortality rates were 1.1% (n = 11) during in-hospital admission, 1.8% (n = 18) at 30 days, 2.7% (n = 27) at 90 days, and 13.3% (n = 129) at 2 years. Lost to follow-up rate at 2 years was 3.3%. We found that CCI was consistently the dominant factor in predicting both short- and long-term mortality. A CCI score of 5 was identified as the inflection point above which comorbidity at baseline presented a greater risk of mortality than a delay in surgery. CONCLUSION: Our analysis showed that CCI is the dominant predictor of both short- and long-term mortality compared with delay in surgery. The effect of CCI is vital in the prognostication of mortality in patients surgically treated for hip fractures.
Authors: Nader Paksima; Kenneth J Koval; Gina Aharanoff; Michael Walsh; Erik N Kubiak; Joseph D Zuckerman; Kenneth A Egol Journal: Bull NYU Hosp Jt Dis Date: 2008
Authors: Suzanne E Bentler; Li Liu; Maksym Obrizan; Elizabeth A Cook; Kara B Wright; John F Geweke; Elizabeth A Chrischilles; Claire E Pavlik; Robert B Wallace; Robert L Ohsfeldt; Michael P Jones; Gary E Rosenthal; Fredric D Wolinsky Journal: Am J Epidemiol Date: 2009-10-04 Impact factor: 4.897