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Record W3096439888 · doi:10.1097/jsa.0000000000000292

Chapter 6: Attritional Glenoid Bone Loss in the Shoulder: Operative Considerations

2020· review· en· W3096439888 on OpenAlexaff
Sara Sparavalo, Ivan Wong

Bibliographic record

VenueSports Medicine and Arthroscopy Review · 2020
Typereview
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsDalhousie UniversityNova Scotia Health Authority
Fundersnot available
KeywordsMedicineSurgerySoft tissueComplicationAnterior shoulderLatarjet procedureGold standard (test)Bankart repairRadiology

Abstract

fetched live from OpenAlex

Patients with recurrent anterior shoulder instability often have glenoid bone loss present in addition to soft tissue pathologies. It is known that patients with significant glenoid bone loss are best treated with a boney augmentation procedure as opposed to a soft tissue Bankart repair because of the high rate of recurrent instability that results from a Bankart repair. Although the Latarjet technique has been the gold-standard treatment for patients with glenoid bone loss because of the low incidence of recurrent instability, it has a high complication rate and a steep learning curve. Herein, the authors present the technique and outcomes for arthroscopic anatomic glenoid reconstruction that has a similar complication rate to the Bankart repair but with a low recurrence rate similar to the Latarjet. This procedure is safe, has a short learning curve, low recurrence rate, and positive patient-reported outcomes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.911
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.114
GPT teacher head0.427
Teacher spread0.313 · 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 teacher head, not a consensus.

Study designOther design
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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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