Abstract

BackgroundRevision total hip arthroplasty (RHA) has been associated with greater morbidity and length of stay (LOS) compared to primary total hip arthroplasty. Despite this, few validated metrics exist for risk stratification in RHA cohorts. The Charlson Comorbidity Index (CCI) has been associated with complications in total hip arthroplasty, but its utility in revision surgery remains unexplored. The purpose of this study was to examine the relationship between preoperative CCI and a variety of outcome metrics following RHA. MethodsThe National Surgical Quality Improvement Program database was used to identify all patients undergoing aseptic RHA between 2006 and 2013. A variety of demographics and perioperative variables were collected. Modified CCI scores were computed for each patient based on a validated formula incorporating comorbidities found in the National Surgical Quality Improvement Program database. Outcome variables of interest included mortality, major postoperative complications, minor adverse events, incidence of transfusion, and prolonged LOS. Perioperative factors were tested for association with these outcomes using bivariate analysis and significant variables were then incorporated into a logistic regression model to explore the relationship between preoperative CCI scores and postoperative events. ResultsIn a multivariable regression model controlling for the significant perioperative variables, operative time, and American Society of Anesthesiologists classification, higher CCI scores were significantly associated with mortality (odds ratio [OR] 1.89, 95% confidence interval [CI] 1.64-2.18, P < .001), major complications (OR 1.12, 95% CI 1.05-1.20, P = .001), minor complications (OR 1.53, 95% CI 1.39-1.69, P < .001), transfusions (OR 1.14, 95% CI 1.09-1.20, P < .001), and prolonged LOS (OR 1.32, 95% CI 1.26-1.39, P < .001). ConclusionHigher preoperative CCI scores were independent risk factors for numerous complications. This highlights the potential utility of the CCI in risk stratification for RHA populations.

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