M C S Inacio1, N L Pratt2, E E Roughead2, S E Graves3. 1. Quality Use of Medicines and Pharmacy Research Centre, Medicine and Device Surveillance Centre of Research Excellence, Sansom Institute, School of Pharmacy and Medical Sciences, University of South Australia, GPO Box 2471, Adelaide 5001, South Australia, Australia. Electronic address: maria.inacio@unisa.edu.au. 2. Quality Use of Medicines and Pharmacy Research Centre, Medicine and Device Surveillance Centre of Research Excellence, Sansom Institute, School of Pharmacy and Medical Sciences, University of South Australia, GPO Box 2471, Adelaide 5001, South Australia, Australia. 3. Australian Orthopaedic Association, National Total Joint Replacement Registry, Level 6, Bice Building, Royal Adelaide Hospital, The University of Adelaide, Adelaide 5005, SA, Australia.
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.
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.
Authors: Alex H S Harris; Alfred C Kuo; Yingjie Weng; Amber W Trickey; Thomas Bowe; Nicholas J Giori Journal: Clin Orthop Relat Res Date: 2019-02 Impact factor: 4.176
Authors: Mhairi M Kerr; Stephen E Graves; Katherine M Duszynski; Maria C Inacio; Richard N de Steiger; Ian A Harris; Ilana N Ackerman; Louisa R Jorm; Michelle F Lorimer; Aarti Gulyani; Nicole L Pratt Journal: Clin Orthop Relat Res Date: 2021-10-01 Impact factor: 4.755