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Methodological Challenges in Predicting Periprosthetic Joint Infection Treatment Outcomes: A Narrative Review.
Naufal, Elise; Wouthuyzen-Bakker, Marjan; Babazadeh, Sina; Stevens, Jarrad; Choong, Peter F M; Dowsey, Michelle M.
Afiliación
  • Naufal E; Department of Surgery, St Vincent's Hospital Melbourne, University of Melbourne, Fitzroy, VIC, Australia.
  • Wouthuyzen-Bakker M; Department of Medical Microbiology and Infection Prevention, University Medical Center Groningen, University of Groningen, Groningen, Netherlands.
  • Babazadeh S; Department of Surgery, St Vincent's Hospital Melbourne, University of Melbourne, Fitzroy, VIC, Australia.
  • Stevens J; Department of Orthopaedics, St Vincent's Hospital Melbourne, Fitzroy, VIC, Australia.
  • Choong PFM; Department of Surgery, St Vincent's Hospital Melbourne, University of Melbourne, Fitzroy, VIC, Australia.
  • Dowsey MM; Department of Orthopaedics, St Vincent's Hospital Melbourne, Fitzroy, VIC, Australia.
Front Rehabil Sci ; 3: 824281, 2022.
Article en En | MEDLINE | ID: mdl-36188976
ABSTRACT
The management of periprosthetic joint infection (PJI) generally requires both surgical intervention and targeted antimicrobial therapy. Decisions regarding surgical management-whether it be irrigation and debridement, one-stage revision, or two-stage revision-must take into consideration an array of factors. These include the timing and duration of symptoms, clinical characteristics of the patient, and antimicrobial susceptibilities of the microorganism(s) involved. Moreover, decisions relating to surgical management must consider clinical factors associated with the health of the patient, alongside the patient's preferences. These decisions are further complicated by concerns beyond mere eradication of the infection, such as the level of improvement in quality of life related to management strategies. To better understand the probability of successful surgical treatment of a PJI, several predictive tools have been developed over the past decade. This narrative review provides an overview of available clinical prediction models that aim to guide treatment decisions for patients with periprosthetic joint infection, and highlights key challenges to reliably implementing these tools in clinical practice.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Aspecto: Patient_preference Idioma: En Revista: Front Rehabil Sci Año: 2022 Tipo del documento: Article País de afiliación: Australia

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Aspecto: Patient_preference Idioma: En Revista: Front Rehabil Sci Año: 2022 Tipo del documento: Article País de afiliación: Australia
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