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Record W2093524388 · doi:10.1007/s11999-013-3436-2

Remplissage Versus Latarjet for Engaging Hill-Sachs Defects Without Substantial Glenoid Bone Loss: A Biomechanical Comparison

2014· article· en· W2093524388 on OpenAlexaff
Ryan M. Degen, Joshua W. Giles, James A. Johnson, George S. Athwal

Bibliographic record

VenueClinical Orthopaedics and Related Research · 2014
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsSt Joseph's Health Care
Fundersnot available
KeywordsLatarjet procedureMedicineCoracoidCadaveric spasmOrthodonticsDislocationSurgeryComposite material

Abstract

fetched live from OpenAlex

BACKGROUND: Recurrent shoulder instability is commonly associated with Hill-Sachs defects. These defects may engage the glenoid rim, contributing to glenohumeral dislocation. Two treatment options to manage engaging Hill-Sachs defects are the remplissage procedure, which fills the defect with soft tissue, and the Latarjet procedure, which increases glenoid arc length. Little evidence exists to support one over the other. QUESTIONS/PURPOSES: We performed a biomechanical comparison of the remplissage procedure to the traditional Latarjet coracoid transfer for management of engaging Hill-Sachs defects in terms of joint stiffness (resistance to anterior translation), ROM, and frequency of dislocation. METHODS: Eight cadaveric specimens were tested on a shoulder instability simulator. Testing was performed with a 25% Hill-Sachs defect with an intact glenoid and after remplissage and Latarjet procedures. Joint stiffness, internal-external rotation ROM, and frequency of dislocation were assessed. Additionally, horizontal extension ROM was measured in composite glenohumeral abduction. RESULTS: After remplissage, stiffness increased in adduction with neutral rotation (12.7 ± 3.7 N/mm) relative to the Hill-Sachs defect state (8.7 ± 3.3 N/mm; p = 0.016). The Latarjet procedure did not affect joint stiffness (p = 1.0). Internal-external rotation ROM was reduced in abduction after the Latarjet procedure (49° ± 14°) compared with the Hill-Sachs defect state (69° ± 17°) (p = 0.009). Horizontal extension was reduced after remplissage (16° ± 12°) relative to the Hill-Sachs defect state (34° ± 8°) (p = 0.038). With the numbers available, there was no difference between the procedures in terms of the frequency of dislocation after reconstruction: 84% of specimens (27 of 32 testing scenarios) stabilized after remplissage, while 94% of specimens (30 of 32 testing scenarios) stabilized after the Latarjet procedure. CONCLUSIONS: Both procedures proved effective in reducing the frequency of dislocation in a 25% Hill-Sachs defect model, while neither procedure consistently altered joint stiffness. CLINICAL RELEVANCE: In the treatment of shoulder instability with a humeral head bone defect and an intact glenoid rim, this study supports the use of both the remplissage and Latarjet procedures. Clinical studies and larger cadaveric studies powered to detect differences in instability rates are needed to evaluate these procedures in terms of their comparative efficacy at preventing dislocation, as any differences between them seem likely to be small.

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)0.002
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 score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.183
GPT teacher head0.490
Teacher spread0.306 · 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

Citations48
Published2014
Admission routes1
Has abstractyes

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