Identification of Independent Predictors of Increased 90-Day Complication and Revision Rates Following Total Elbow Arthroplasty

Introduction Total elbow arthroplasty (TEA) is an increasingly popular surgical option for many debilitating conditions of the elbow. There currently exists a paucity of literature regarding patient and hospital factors that lead to inferior outcomes following TEA. The purpose of this study is to identify independent predictors of increased complication and revision rates following TEA. Methods The National Readmissions Database (NRD) was queried from 2011 to 2018 to identify all cases of TEA (n = 8932). Relevant patient demographic factors, comorbidities, and hospital characteristics were identified and run in a univariate binomial logistic regression model. All significant variables were included in a multivariate binomial logistic regression model for data analysis. Results Independent predictors of increased complication rates included age, female sex, Medicare and Medicaid payer status, medium bed-sized center, and 18 of 34 medical comorbidities (all P