Methodological Challenges in Predicting Periprosthetic Joint Infection Treatment Outcomes: A Narrative Review

Elise Naufal*, Marjan Wouthuyzen-Bakker, Sina Babazadeh, Jarrad Stevens, Peter F.M. Choong, Michelle M. Dowsey

*Corresponding author for this work

    Research output: Contribution to journalReview articlepeer-review

    3 Citations (Scopus)
    10 Downloads (Pure)

    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.

    Original languageEnglish
    Article number824281
    Number of pages7
    JournalFrontiers in Rehabilitation Sciences
    Volume3
    DOIs
    Publication statusPublished - 11-Jul-2022

    Keywords

    • arthroplasty
    • periprosthetic joint infection (PJI)
    • predictive models
    • prognostic models
    • risk prediction

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