Analyses using population-based health administrative data can return erroneous results if case identification is inaccurate ("misclassification bias"). An acetabular fracture (AF) prediction model using administrative data decreased misclassification bias compared to identifying AFs using diagnostic codes. This study measured the accuracy of this AF prediction model in another hospital.
View Article and Find Full Text PDFImportance: Unstable chest wall injuries have high rates of mortality and morbidity. In the last decade, multiple studies have reported improved outcomes with operative compared with nonoperative treatment. However, to date, an adequately powered, randomized clinical trial to support operative treatment has been lacking.
View Article and Find Full Text PDFObjectives: To determine the impact of dedicated orthopaedic trauma room (DOTR) implementation on operating room efficiency and finances.
Design: Retrospective cost-analysis.
Setting: Single midsized academic-affiliated community hospital in Toronto, Canada.
Background: The number of periprosthetic fractures above a total knee arthroplasty continues to increase. These fractures are associated with a high risk of morbidity and mortality. Techniques for addressing these fractures include open reduction internal fixation (ORIF) and revision arthroplasty, including distal femoral replacement (DFR).
View Article and Find Full Text PDFBackground: Geriatric patients are the most rapidly growing cohort of patients sustaining acetabular fractures (AFs). The purpose of this study was to examine the risk of a secondary total hip arthroplasty (THA) in older patients (>60 year old) with a prior AF open reduction internal fixation (ORIF) compared with younger patients (<60 year old) with an AF ORIF on a large population level.
Methods: Using administrative health care data from 1996 to 2010 inclusive of all 202 hospitals in Ontario, Canada, all adult patients with an AF ORIF and a minimum of two year follow-up were identified and included.