External Validation Demonstrates Limited Clinical Utility of a Preoperative Prognostic Calculator for Periprosthetic Joint Infection

Monárrez, Rubén; Maltenfort, Mitchell; Figoni, Andrew; Szapary, Hannah J.; Chen, Antonia F.; Hansen, Erik N.; Kheir, Michael M.

doi:10.1016/j.arth.2021.02.067

Cited by 1 publication

(1 citation statement)

References 26 publications

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“…The CRIME-80 score (which stands for COPD, CRP >150 mg/L, Rheumatoid Arthritis, Indication prosthesis: fracture, Male, Exchange of mobile components and Age 80 years) was shown to have relatively poor discriminative performance (AUC 0.61, 95% CI 0.50–0.73) ( 20 ). The model developed by Kheir et al showed a more varied performance when externally validated on two datasets (AUC 0.80 95% CI 0.70–0.90 and AUC 0.60 95% CI 0.50–0.69) ( 21 ). Importantly, to date no published external validations of these predictive tools have reported on the calibration of these models.…”

Section: The Process Of Prediction: Model Development and Validationmentioning

confidence: 99%

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

Naufal¹,

Wouthuyzen-Bakker²,

Babazadeh³

et al. 2022

Front. Rehabilit. Sci.

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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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Section: The Process Of Prediction: Model Development and Validationmentioning

confidence: 99%

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

Naufal¹,

Wouthuyzen-Bakker²,

Babazadeh³

et al. 2022

Front. Rehabilit. Sci.

View full text Add to dashboard Cite

show abstract

External Validation Demonstrates Limited Clinical Utility of a Preoperative Prognostic Calculator for Periprosthetic Joint Infection

Cited by 1 publication

References 26 publications

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

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

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