Agreement Analysis Among Hip and Knee Periprosthetic Joint Infections Classifications

<b>Background/Objectives</b>: A missed periprosthetic joint infection (PJI) diagnosis can lead to implant failure. However, to date, no gold standard for PJI diagnosis exists, although several classification scores have been developed in the past years. The primary objective of the study was the evaluation of inter-rater reliability between five PJI classification systems when defining a patient who is infected. Two secondary outcomes were further examined: the inter-rater reliability assessed by comparing the classifications in pairs, and the evaluation of each classification system within the subcategories defined by the World Association against Infection in Orthopaedics and Trauma (WAIOT) definition. <b>Methods</b>: Retrospectively collected data on patients with knee and hip PJIs were used to assess the agreement among five PJI scoring systems: the Musculoskeletal Infection Society (MSIS) 2013 definition, the Infection Consensus Group (ICG) 2018 definition, the European Bones and Joints Infection Society (EBJIS) 2018 definition, the WAIOT definition, and the EBJIS 2021 definition. <b>Results</b>: In total, 203 patients with PJI were included in the study, and the agreement among the examined scores was 0.90 (Krippendorff's alpha = 0.81; <i>p</i>-value < 0.001), with the MSIS 2013 and ICG 2018 classification systems showing the highest agreement (Cohen's Kappa = 0.91; <i>p</i>-value < 0.001). <b>Conclusions</b>: There is a strong agreement between the major PJI classification systems. However, a subset of patients (<i>n</i> = 11, 5.42%) still falls into a diagnostic grey zone, especially in cases of low-grade infections. This highlights the need for enhanced diagnostic criteria that incorporate tools that are available even with limited resources, and the potential of artificial intelligence-based techniques in improving early detection and management of PJIs.

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Publication Details

Journal
Diagnostics
Published
2025-05-04
DOI
https://doi.org/10.3390/diagnostics15091172
Primary Topic
Orthopedic Infections and Treatments
Type
article
Field-Weighted Citation Impact
0.00

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article

Agreement Analysis Among Hip and Knee Periprosthetic Joint Infections Classifications

Guido Grappiolo, Alberto Bulgarelli, Caterina Rocchi, Marco Di Maio et al.
Diagnostics
Orthopedic Infections and Treatments
article

Agreement Analysis Among Hip and Knee Periprosthetic Joint Infections Classifications

Guido Grappiolo, Alberto Bulgarelli, Caterina Rocchi, Marco Di Maio, Mattia Loppini, Francesco La Camera, Katia Chiappetta
article en

Abstract

<b>Background/Objectives</b>: A missed periprosthetic joint infection (PJI) diagnosis can lead to implant failure. However, to date, no gold standard for PJI diagnosis exists, although several classification scores have been developed in the past years. The primary objective of the study was the evaluation of inter-rater reliability between five PJI classification systems when defining a patient who is infected. Two secondary outcomes were further examined: the inter-rater reliability assessed by comparing the classifications in pairs, and the evaluation of each classification system within the subcategories defined by the World Association against Infection in Orthopaedics and Trauma (WAIOT) definition. <b>Methods</b>: Retrospectively collected data on patients with knee and hip PJIs were used to assess the agreement among five PJI scoring systems: the Musculoskeletal Infection Society (MSIS) 2013 definition, the Infection Consensus Group (ICG) 2018 definition, the European Bones and Joints Infection Society (EBJIS) 2018 definition, the WAIOT definition, and the EBJIS 2021 definition. <b>Results</b>: In total, 203 patients with PJI were included in the study, and the agreement among the examined scores was 0.90 (Krippendorff's alpha = 0.81; <i>p</i>-value < 0.001), with the MSIS 2013 and ICG 2018 classification systems showing the highest agreement (Cohen's Kappa = 0.91; <i>p</i>-value < 0.001). <b>Conclusions</b>: There is a strong agreement between the major PJI classification systems. However, a subset of patients (<i>n</i> = 11, 5.42%) still falls into a diagnostic grey zone, especially in cases of low-grade infections. This highlights the need for enhanced diagnostic criteria that incorporate tools that are available even with limited resources, and the potential of artificial intelligence-based techniques in improving early detection and management of PJIs.

DiagnosticsVol. 15(9)
Humanitas University (IT), University of Trieste (IT), IRCCS Humanitas Research Hospital (IT)
Ministero della Salute
Partnerships for the goals
Openalex Percentile: Top 83%
Orthopedic Infections and Treatments
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