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Record W4362691968 · doi:10.1177/03635465231164141

Outcomes of Open Versus Arthroscopic Treatment of HAGL Tears

2023· article· en· W4362691968 on OpenAlexaboutno aff
Simon Lee, Aaron J. Krych, Annalise M. Peebles, Danielle Rider, Travis J. Dekker, Justin W. Arner, Ryan J. Whalen, Matthew T. Provencher

Bibliographic record

VenueThe American Journal of Sports Medicine · 2023
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSubluxationSurgeryArthroscopyPhysical examinationRange of motionRetrospective cohort studyTearsPresentation (obstetrics)LigamentOpen surgery

Abstract

fetched live from OpenAlex

Background: Lesions that involve humeral avulsions of the glenohumeral ligament (HAGLs), although less common, are primary contributors to recurrent events of dislocation and subluxation of the glenohumeral joint. Purpose: To describe the clinical presentation, examination, and surgical outcomes of patients presenting with HAGL lesions who underwent repair using an arthroscopic or open technique. Study Design: Cohort study; Level of evidence, 3. Methods: A multicenter retrospective review of prospectively collected data was performed of skeletally mature patients without glenohumeral arthritis who presented with HAGL lesions and subsequently underwent arthroscopic or open repair between 2005 and 2017. Independent variables included patient characteristics, clinical presentation, physical examination findings, and arthroscopic findings. Dependent variables included pre- and postoperative Single Assessment Numeric Evaluation (SANE) score, Western Ontario Shoulder Instability Index (WOSI) score, and range of motion outcomes. Results: Eighteen patients diagnosed with a HAGL lesion who underwent primary arthroscopic repair (n = 7) or open repair (n = 11) were included. There were 17 male patients and 1 female patient with a mean age of 24.9 years (range, 16-38 years). Mean follow-up duration was 50.9 months (range, 24-160 months). Seventeen patients (94.4%) reported pain as the most common symptom, and 7 (38.9%) reported sensation of instability. Scores significantly improved from pre- to postoperative for the arthroscopic and open groups ( P < .001): SANE (mean ± SD; arthroscopic, 30.7 ± 15.7 to 92.1 ± 12.2; open, 45.5 ± 8.50 to 90.7 ± 5.24) and WOSI (arthroscopic, 51.4 ± 11.4 to 2.49 ± 3.70; open, 45.5 ± 7.37 to 11.5 ± 5.76). The magnitude of improvement in SANE scores was significantly higher for patients treated arthroscopically (Δ60.0; open, Δ46.5; P = .012). Postoperative WOSI scores were also significantly better in the arthroscopic cohort (2.49 ± 3.70; open, 11.5 ± 5.76; P = .00094). Conclusion: Symptomatic HAGL tears present primarily with pain as opposed to instability, necessitating a high index of suspicion for injury. The tears may be treated successfully with an arthroscopic or open technique with significant improvements in patient-reported outcomes and stability.

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)0.005
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.063
GPT teacher head0.404
Teacher spread0.341 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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