Evaluation of three co-morbidity measures to predict mortality in patients undergoing total joint arthroplasty

Abstract

Objective: To evaluate the 90 days and 1 year mortality predictive ability of the RxRisk-V, Charlson, and Elixhauser co-morbidity measures in total hip arthroplasty (THA) and total knee arthroplasty (TKA) patients. Method: A retrospective study of 11,848 THAs and 18,972 TKAs (2001–2002) was conducted. Death within 90 days and 1 year of the surgery were the main endpoints. Co-morbidity measures were calculated using either medication or hospitalisation history. Logistic regression models were employed and discrimination and calibration were assessed. Specifically, models with unweighted and weighted measure scores, models with the specific conditions, and a model combining conditions identified by all measures were assessed. Results: In THAs, the best performing prediction models included co-morbidities from all three measures (90 days: c = 0.84, P = 0.284, 1 year: c = 0.79, P = 0.158). Individually, the model with Charlson conditions performed best at 90 days mortality (c = 0.80, P = 0.777) and the Charlson and Elixhauser performed similarly at 1 year (both c = 0.77, P > 0.05). In TKAs, the best performing prediction model included co-morbidities from all measures (90 days: c = 0.82, P = 0.349, 1 year: c = 0.78, P = 0.873). Individually, the model with Elixhauser conditions performed best with 90 days mortality (c = 0.79, P = 0.435) and all performed similarly at 1 year (c = 0.74–0.75, all P > 0.05). Conclusions: A combined model with co-morbidities identified by the Elixhauser, Charlson, and RxRisk-V was the best mortality prediction model. The RxRisk-V did not perform as well as the others. Because of the Elixhauser and Charlson's similar performance we suggest basing the choice of measurement use on factors such as the need of specific conditions and modelling limitations.