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Record W1513673091 · doi:10.1016/j.eats.2015.01.013

Lateral Decubitus All‐Arthroscopic Latarjet Procedure for Treatment of Shoulder Instability

2015· article· en· W1513673091 on OpenAlexaff
Matthew R. Lewington, Nathan Urquhart, Ivan Wong

Bibliographic record

VenueArthroscopy Techniques · 2015
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsCapital District Health AuthorityNova Scotia Health AuthorityDalhousie University
FundersSmith and Nephew
KeywordsMedicineLatarjet procedureCoracoidSurgeryAnterior shoulderRange of motion

Abstract

fetched live from OpenAlex

Shoulder instability can be a challenging condition to treat when it becomes refractory to soft-tissue procedures or when bone loss exceeds 25% to 27% of the glenoid. The Bristow-Latarjet procedure has been developed and popularized to deal with these concerns. Traditionally, the procedure has been performed as an open approach; however, this has been recently supplanted by novel arthroscopic techniques. We present a technique for the procedure performed with the patient in a semi-lateral decubitus position that assists with optimal graft placement on the native glenoid. We use the cannulated Bristow-Latarjet Instability Shoulder System (DePuy Mitek, Raynham, MA). After a diagnostic arthroscopic evaluation, we use multiple arthroscopic anterior portals to debride the rim of the glenoid. The coracoid is prepared and taken down arthroscopically, and the cannulated guide is attached and advanced through an arthroscopically created subscapularis split. With the shoulder held in a reduced position, we are then able to drill and anchor the graft to the native glenoid. The patient is able to begin gentle range-of-motion exercises immediately postoperatively.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.077
GPT teacher head0.396
Teacher spread0.319 · 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 designCase report
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
Published2015
Admission routes1
Has abstractyes

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