Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/133643
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Type: Journal article
Title: Predicting infections after total joint arthroplasty using a prescription based comorbidity measure
Author: Inacio, M.C.S.
Pratt, N.L.
Roughead, E.E.
Graves, S.E.
Citation: Journal of Arthroplasty, 2015; 30(10):1692-1698
Publisher: Elsevier
Issue Date: 2015
ISSN: 0883-5403
1532-8406
Statement of
Responsibility: 
Maria C.S.Inacio, Nicole L.Pratt, Elizabeth E.Roughead, Stephen E.Graves ... et al.
Abstract: This study evaluated the association and predictive ability of co-morbidities measured by RxRisk-V, Elixhauser and Charlson measures and post-total hip (THA) and total knee arthroplasties (TKA) infection. THAs and TKAs (2001–2012) were identified using the Australian Department of Veterans’ Affairs data. Infections within 90 days post-surgery were the study endpoint. Co-morbidities were identified using pharmacy (RxRisk-V) and hospitalization history (Elixhauser, Charlson). Of the 11,848 THAs, 3.1% (N = 364) had infections and out of 18,972 TKAs 3.4% (N = 648). Comorbidity burden and specific conditions were associated with infection likelihood. RxRisk-V performed better than other measures, but none had high predictive ability and differences were small. The best performing infection prediction models resulted when a combination of conditions identified by all measures was used.
Keywords: co-morbidities; total knee arthroplasty; total hip arthroplasty; RxRisk-V; pharmacy data
Rights: © 2015 Elsevier Inc. All rights reserved.
DOI: 10.1016/j.arth.2015.05.004
Grant ID: http://purl.org/au-research/grants/nhmrc/1040938
http://purl.org/au-research/grants/nhmrc/1035889
Published version: http://dx.doi.org/10.1016/j.arth.2015.05.004
Appears in Collections:Orthopaedics and Trauma publications

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