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Record W4416809071 · doi:10.2106/jbjs.25.01070

Consensus Recommendations and Insights on Infection

2025· article· en· W4416809071 on OpenAlexaff
Emil H. Schemitsch

Bibliographic record

VenueJournal of Bone and Joint Surgery · 2025
Typearticle
Languageen
FieldMedicine
TopicOrthopedic Infections and Treatments
Canadian institutionsWestern University
Fundersnot available
KeywordsDelphi methodBest practiceConsensus conferenceMEDLINEDelphiGold standard (test)Quality (philosophy)Executive summary

Abstract

fetched live from OpenAlex

Commentary Musculoskeletal procedures performed for arthritis and other degenerative conditions can greatly improve pain, function, and quality of life. However, some patients experience major complications, with musculoskeletal infection being among the most devastating. Infection places a substantial burden on both patients and health-care systems globally, and there is universal interest in reaching consensus on the best practices for prevention, diagnosis, and treatment. Infection management is often challenging, requiring repeat surgical procedures, prolonged hospitalizations, and extended antimicrobial therapy with a substantial risk of treatment failure. Moreover, the management of suspected and/or established musculoskeletal infection remains controversial, varies by anatomic region, and lacks an accepted gold standard for diagnosis and treatment in the preoperative, intraoperative, and postoperative periods. Treatment selection remains highly variable globally and is influenced by patient factors, surgeon preference, and institutional and regional practices. Achieving international consensus on approaches to the prevention, diagnosis, and treatment of infection is crucial for optimizing patient care. In response to this tremendous need, the 3rd International Consensus Meeting (ICM) on Infection was held in Istanbul, Türkiye, from May 8 to 10, 2025, and included 857 delegates from >100 countries, with >300 questions divided across General, Hip and Knee, Biofilm, Shoulder, and Spine subsections. The article by the International Consensus Meeting Executive Committee presents an overview of the methodology behind the ICM and a summary and analysis of the top 10 questions asked that had the highest quality of evidence available to answer them. The authors report on the iterative Delphi process that was used to identify the >300 questions, which were ranked in order of importance; the answers to those questions, which were obtained using a standardized process for evidence synthesis; and the level of consensus on the findings for each question. The top 10 questions with the highest quality of evidence available to answer them were mainly related to intraoperative management. Despite having the best evidence, the answers to these questions had a wide range of consensus, ranging from low/no consensus to unanimity. Only 4 of the 10 questions had a unanimous response, and, of those, only 1 had findings showing a clear effect in reducing the risk of infection. For that question, the consensus was to strongly recommend cephalosporins, particularly cefazolin, for first-line prophylaxis in primary arthroplasty. This recommendation was based on high-quality evidence showing a significant reduction in infection risk and minimal adverse effects. One of the key strengths of this work is the rigorous >2-year process leading up to the ICM. A major contribution of this work is the finding that there is a wide range of consensus around infection prevention and management, even when the evidence is of higher quality. As highlighted by the authors, a renewed focus on knowledge translation to improve familiarity with the available evidence and to break down barriers to implementation is required to improve patient care, as well as efforts that take into account local contextual and resource-based limitations. Such efforts will be critically important when trying to apply recommendations globally, particularly when a great deal of the higher-quality evidence has been created in idealized settings. There are several limitations that should be noted when reviewing this work. First, the authors present the top 10 questions supported by the most high-quality evidence, but it is unclear how they were able to rank or determine the questions that had the best evidence. Second, it is unclear how the cutoffs for the levels of consensus were obtained. Third, for the general questions related to the overall management of infection, it is unclear how much of the evidence was derived from specific anatomic regions and whether the evidence was as strong for other anatomic regions. In conclusion, the work of the International Consensus Meeting Executive Committee highlights the fact that infection continues to be one of the biggest problems in orthopaedic surgery today, with profound and long-lasting impacts on patients, the health-care system, and society. The consensus gained from the ICM will undoubtedly improve patient care and lead to changes in surgical practice but emphasizes the need for a robust knowledge-translation strategy to maximize the potential gains. There is also an unmet need for much better evidence, as many of the critical questions in this area are still unanswered.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.114
metaresearch head score (Gemma)0.412
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.114
Threshold uncertainty score0.605

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1140.412
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0040.009
Bibliometrics0.0160.011
Science and technology studies0.0050.006
Scholarly communication0.0150.016
Open science0.0110.014
Research integrity0.0310.036
Insufficient payload (model declined to judge)0.0370.016

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.286
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
Has abstractyes

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