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Analysis of institutional authors

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Predicting periprosthetic joint infection: external validation of preoperative prediction models.

Publicated to:J Bone Jt Infect. 9 (5): 231-239 - 2024-01-01 9(5), DOI: 10.5194/jbji-9-231-2024

Authors: Yoon SJ; Jutte PC; Soriano A; Sousa R; Zijlstra WP; Wouthuyzen-Bakker M

Affiliations

Department of Medical Microbiology and Infection Prevention, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands. - Author
Department of Orthopaedic Surgery, Medical Center Leeuwarden, Leeuwarden, The Netherlands. - Author
Department of Orthopaedic Surgery, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands. - Author
Infectious Diseases Service, Clínic Barcelona, University of Barcelona, Barcelona, Spain. - Author
Porto Bone Infection Group (GRIP), Orthopaedic Department, Centro Hospitalar Universitário do Porto, Porto, Portugal. - Author
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Abstract

Introduction: Prediction models for periprosthetic joint infections (PJIs) are gaining interest due to their potential to improve clinical decision-making. However, their external validity across various settings remains uncertain. This study aimed to externally validate promising preoperative PJI prediction models in a recent multinational European cohort. Methods: Three preoperative PJI prediction models - by Tan et al. (2018), Del Toro et al. (2019), and Bülow et al. (2022) - that have previously demonstrated high levels of accuracy were selected for validation. A retrospective observational analysis of patients undergoing total hip arthroplasty (THA) and total knee arthroplasty (TKA) at centers in the Netherlands, Portugal, and Spain between January 2020 and December 2021 was conducted. Patient characteristics were compared between our cohort and those used to develop the models. Performance was assessed through discrimination and calibration. Results: The study included 2684 patients, 60 of whom developed a PJI (2.2 %). Our cohort differed from the models' original cohorts with respect to demographic variables, procedural variables, and comorbidity prevalence. The overall accuracies of the models, measured with the c  statistic, were 0.72, 0.69, and 0.72 for the Tan, Del Toro, and Bülow models, respectively. Calibration was reasonable, but the PJI risk estimates were most accurate for predicted infection risks below 3 %-4 %. The Tan model overestimated PJI risk above 4 %, whereas the Del Toro model underestimated PJI risk above 3 %. Conclusions: The Tan, Del Toro, and Bülow PJI prediction models were externally validated in this multinational cohort, demonstrating potential for clinical application in identifying high-risk patients and enhancing preoperative counseling and prevention strategies.

Keywords
Infectious diseasesOrthopedicsOrthopedics and sports medicineSurgery

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal J Bone Jt Infect due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2024 there are still no calculated indicators, but in 2023, it was in position 94/132, thus managing to position itself as a Q2 (Segundo Cuartil), in the category Infectious Diseases. Notably, the journal is positioned en el Cuartil Q2 para la agencia Scopus (SJR) en la categoría Surgery.

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-05-23:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 2.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 2 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 1.5.
  • The number of mentions on the social network X (formerly Twitter): 2 (Altmetric).
Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Netherlands; Portugal.