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Record W4280622493 · doi:10.1016/j.eats.2022.02.010

Arthroscopic Anterior Glenoid Reconstruction Using a Distal Tibial Allograft Positioned With an Intra‐Articular Guide and Secured With Double‐Button Fixation

2022· article· en· W4280622493 on OpenAlexaff
Jayd Lukenchuk, Tanujan Thangarajah, Kristie D. More, Ivan Wong, Ian K.Y. Lo

Bibliographic record

VenueArthroscopy Techniques · 2022
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsNova Scotia Health AuthorityDalhousie UniversityUniversity of Calgary
FundersSmith and NephewArthrex
KeywordsMedicineDrillSurgeryFixation (population genetics)PercutaneousArticular surfaceLabrumArthroscopyAnatomy

Abstract

fetched live from OpenAlex

Recurrent shoulder instability and its role in bone loss from the anterior glenoid is well recognized throughout the literature. This technique paper presents an all-arthroscopic technique that uses distal tibial allograft and double-button suture fixation to address anterior recurrent shoulder instability. With the patient in the lateral decubitus position, we use the posterior portal to position the double-barrel drill guide tangential to the face of the glenoid, while viewing through the anterosuperolateral portal. We then use the "bullets," which are made through two percutaneous posterior skin incisions of the double-barreled drill. This guide ensures parallel drill tunnels are created 5 mm medial to the glenoid articular surface and 1 cm apart, minimizing risk to the suprascapular nerve caused by a straying medial. We prepare a bone block from allograft distal tibia and place two drill holes to match those drilled in the glenoid vault. The allograft is then shuttled arthroscopically using looped passing wires. Once the final position is confirmed, a tensiometer is used to tension the graft in place. We then reattach the labrum to the native glenoid rim. Our technique creates a reproducible, anatomic, glenoid surface reconstruction for anterior glenoid bone loss in recurrent instability.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.779

Codex and Gemma teacher scores by category

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

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 head0.013
GPT teacher head0.302
Teacher spread0.289 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations6
Published2022
Admission routes1
Has abstractyes

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