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Record W3100652902 · doi:10.1177/2325967120964474

Acromioclavicular Joint Injuries in Professional Ice Hockey Players: Epidemiologic and MRI Findings and Association With Return to Play

2020· article· en· W3100652902 on OpenAlexaff
Lawrence M. White, Jonathan Ehmann, Robert Bleakney, Anthony M. Griffin, John Theodoropoulos

Bibliographic record

VenueOrthopaedic Journal of Sports Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicShoulder and Clavicle Injuries
Canadian institutionsUniversity of TorontoAthletic Edge Sports MedicineMount Sinai Hospital
Fundersnot available
KeywordsIce hockeyMedicineAcromioclavicular jointPhysical therapyMagnetic resonance imagingInjury preventionRetrospective cohort studyPoison controlPhysical medicine and rehabilitationSurgeryRadiologyEmergency medicine

Abstract

fetched live from OpenAlex

Background: Acromioclavicular joint (ACJ) injuries are common in ice hockey players and are traditionally evaluated with conventional radiography, which has recognized limitations in the accurate characterization of the spectrum of soft tissue injuries and severity/grade of injury sustained. Purpose: To evaluate the epidemiologic, clinical, and magnetic resonance imaging (MRI) findings in professional ice hockey players who have sustained acute ACJ injuries. Study Design: Case series; Level of evidence, 4. Methods: A retrospective review was performed of professional National Hockey League (NHL) players referred for MRI evaluation of acute ACJ injuries. All MRI scans were assessed for status of the ACJ, ligamentous stabilizers, and surrounding musculature. MRI-based overall grade of ACJ injury (modified Rockwood grade 1-6) was assigned to each case. Data regarding mechanism of injury, player handedness, clinical features, and return to play were evaluated. Results: Overall, 24 MRI examinations of acute ACJ injuries (23 patients; mean age, 24 years) were reviewed. We found that 50% of injuries were sustained during the first period of play, and in 75% of cases, injuries involved the same side as player shooting handedness. Analysis of MRI scans revealed 29% (7/24) grade 1 ACJ injuries, 46% (11/24) grade 2 injuries, 21% (5/24) grade 3 injuries, and 4% (1/24) grade 5 injuries. Trapezius muscle strains were seen in 79% and deltoid muscle strain in 50% of cases. Nonoperative management was used for 23 injuries; 1 patient (grade 5 injury) underwent acute reconstructive surgery. All players successfully returned to professional NHL competition. Excluding cases with additional injuries or surgery (n = 3) or convalescence extending into the offseason (n = 3), we found that the mean return to play was 21.4 days (7.2 games missed). No statistically significant difference was observed in return to play between nonoperatively treated grade 3 injuries (mean, 28.3 days) and grade 1 or 2 injuries (mean, 20.1 days). However, grade 3 injuries were associated with a greater number of NHL scheduled games missed (mean, 12.7) compared with lower grade injuries (mean, 6.1) ( P = .027). Conclusion: The spectrum of pathology and grading of acute ACJ injuries sustained in professional ice hockey can be accurately assessed with MRI; the majority of injuries observed in this study were low grade (grades 1 and 2). Although grade 3 injuries were associated with a greater number of games missed, similar return-to-play results were observed between nonoperatively treated grade 3 and grade 1 or 2 ACJ injuries.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.319
Teacher spread0.302 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations17
Published2020
Admission routes1
Has abstractyes

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