MétaCan
Menu
Back to cohort
Record W2075883343 · doi:10.1016/j.arthro.2012.09.007

Classic Versus Congruent Coracoid Positioning During the Latarjet Procedure: An In Vitro Biomechanical Comparison

2013· article· en· W2075883343 on OpenAlexaff
Harm W. Boons, Joshua W. Giles, Ilia Elkinson, James A. Johnson, George S. Athwal

Bibliographic record

VenueArthroscopy The Journal of Arthroscopic and Related Surgery · 2013
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsSt Joseph's Health CareWestern University
FundersArthrex
KeywordsLatarjet procedureCoracoidKinematicsOrthodonticsComputer scienceAnatomyBiologyMedicinePhysics

Abstract

fetched live from OpenAlex

PURPOSE: The purpose of this biomechanical study was to compare the classic Latarjet technique and congruent-arc modification with respect to glenohumeral stability, joint stiffness, translation, and range of motion. METHODS: Eight cadaveric forequarters were tested on a shoulder simulator that applied loads independently to the conjoint tendon, long head of biceps, rotator cuff, and deltoid. The test conditions included: intact, 30% glenoid defect, and reconstruction of the defect with the classic and congruent Latarjets. The Latarjet techniques were randomly ordered, with the outcome variables being anterior dislocation, glenohumeral translation, rotational range of motion, and joint stiffness. RESULTS: All 8 specimens dislocated after creation of a 30% glenoid defect. The classic Latarjet stabilized 7 of 8 specimens, whereas the congruent-arc modification stabilized all specimens (8/8). In abduction neutral rotation, there was no difference in joint translation between techniques (P = .613). In abduction external rotation, there was significantly greater anterior humeral head translation after the congruent technique than after the classic (9.9 and 6.5 mm, respectively, P = .013). Rotational range of motion was significantly reduced after classic (-25.8°) and congruent (-22.2°) transfers as compared with the 30% defect (P ≤ .041). Joint stiffness in the abducted, externally rotated position was significantly reduced in the 30% defect as compared with intact (P = .012), congruent (P = .015), and classic (P < .001) conditions. In all abduction positions, the intact was not significantly different from the Latarjet techniques, and the techniques did not significantly differ from each other (P ≥ .102). CONCLUSIONS: The classic and congruent-arc Latarjet techniques restore shoulder stability and motion in cases of considerable bone loss. The techniques do not substantially differ in rotational range of motion or joint stiffness. The congruent-arc technique, however, does result in significantly greater anterior humeral head translation, as compared with the classic technique, before reaching a stable non-dislocated endpoint. CLINICAL RELEVANCE: On the basis of this biomechanical model, both the classic and congruent-arc Latarjet techniques can be used to stabilize a shoulder with substantial glenoid bone loss. Further clinical and biomechanical studies are required to determine if particular clinical circumstances exist where 1 technique has an advantage over the other.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0020.000

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 head0.021
GPT teacher head0.299
Teacher spread0.278 · 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 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

Citations58
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueArthroscopy The Journal of Arthroscopic and Related SurgerySame topicShoulder Injury and TreatmentFrench-language works237,207