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Record W4406750128 · doi:10.1177/23259671241305409

Management of Labral Tears in the Hip: A Consensus Statement

2025· article· en· W4406750128 on OpenAlexaffabout
Bogdan A. Matache, Étienne L. Belzile, Olufemi R. Ayeni, Luc De Garie, Ryan M. Degen, Richard Goudie, Martin Heroux, Marie-Josée Klett, Erika Persson, Ivan Wong, Firas Al-Rawi, P. H. Baylis, Paul E. Beaulé, R Blanchet, Jordan Buchko, Pierre Collin, Jason Crookham, Eoghan T. Hurley, Kelly Johnston, Moin Khan, Diane K. Lambert, Claire LeBlanc, Devin B. Lemmex, Patrick Ling, Parth Lodhia, Billy Longland, R. Kyle Martin, Mark O. McConkey, Bob McCormack, Mickey Moroz, Marie‐Lyne Nault, Ross Outerbridge, Julie Peltz, Anita Pozgay, David C. Reid, Scott Shallow, Ryan Shields, Allison Tucker, Nathan Urquhart, Jarret M. Woodmass

Bibliographic record

VenueOrthopaedic Journal of Sports Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicHip disorders and treatments
Canadian institutionsUniversity of ManitobaUniversity of British ColumbiaPan Am ClinicQueen's UniversitySaskatoon Medical ImagingWestern UniversityUniversity of TorontoDalhousie UniversityUniversity of CalgaryCanadian Sport Centre PacificFowler Kennedy Sport Medicine ClinicUniversity of AlbertaUniversité de MontréalUniversity of SaskatchewanKamloops Art GalleryUniversité LavalMcMaster UniversityOttawa HospitalAlgonquin CollegeMcGill UniversityUniversity of Ottawa
Fundersnot available
KeywordsMedicineGroinPhysical therapyDelphi methodConsensus conferenceStatement (logic)RehabilitationSurgery

Abstract

fetched live from OpenAlex

Background: Inconsistencies in the workup of labral tears in the hip have been shown to result in a delay in treatment and an increased cost to the medical system. Purpose: To establish consensus statements among Canadian nonoperative/operative sports medicine physicians via a modified Delphi process on the diagnosis, nonoperative and operative management, and rehabilitation and return to play (RTP) of those with labral tears in the hip. Study Design: A consensus statement. Methods: A total of 40 sports medicine physicians (50% orthopaedic surgeons) were selected for participation based on their level of expertise in the field. Experts were assigned to 1 of 4 balanced working groups defined by specific subtopics of interest. Consensus, strong consensus, and unanimous consensus were defined as achieving 80% to 89%, 90% to 99%, and 100% agreement with a proposed statement, respectively. Results: There was a unanimous consensus that several prognostic factors-including age, pain severity, dysplasia, and degenerative changes-should be taken into consideration with regard to the likelihood of surgical success. There was strong agreement that the cluster of symptoms of anterior groin pain, pain in hyperflexion, and sharp catching pain with rotation make a diagnosis of a labral tear more likely, that radiographs-including a minimum of a standing anteroposterior pelvis and 45° Dunn view-should be obtained in all patients presenting with a suspected labral tear, that a diagnostic injection should be performed if there is uncertainty that the pain is intra-articular in origin, and that a minimum of 6 months should elapse after surgical treatment before reinvestigation for persistent symptoms. Conclusion: Overall, 76% of statements reached a unanimous/strong consensus, thus indicating a high level of agreement between nonoperative sports medicine physicians and orthopaedic surgeons on the management of labral tears in the hip. The statements that achieved unanimous consensus included the timing of RTP after surgery, prognostic factors affecting surgical success, and the timing to begin sport-specific training after nonoperative management. There was no consensus on the use of orthobiologics for nonoperative management, indications for bilateral surgery, whether the postoperative range of motion and weightbearing restrictions should be employed, and whether postoperative hip brace usage is required.

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)0.124
metaresearch head score (Gemma)0.125
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.124
Threshold uncertainty score0.654

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1240.125
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.003
Science and technology studies0.0050.004
Scholarly communication0.0040.004
Open science0.0060.008
Research integrity0.0100.009
Insufficient payload (model declined to judge)0.0020.001

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 head0.012
GPT teacher head0.298
Teacher spread0.286 · 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
GenreOther

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".

Quick stats

Citations5
Published2025
Admission routes2
Has abstractyes

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