The biomechanical effectiveness of tendon transfers to restore rotation after reverse shoulder arthroplasty: latissimus versus lower trapezius
Bibliographic record
Abstract
BACKGROUND: The purpose of this biomechanical simulator study was primarily to compare latissimus dorsi to lower trapezius tendon transfers for active external rotation and the pectoralis major transfer for internal rotation after reverse shoulder arthroplasty. Secondarily, the role of humeral component lateralization on transfer function was assessed. METHODS: Eight rotator cuff deficient cadavers underwent reverse shoulder arthroplasty with an adjustable lateralization humeral component. Latissimus dorsi and lower trapezius transfers were compared for active external rotation restoration and pectoralis major transfer for internal rotation restoration. Internal rotation/external rotation torques were measured for each lateralization at varying abduction and internal rotation/external rotation ranges-of-motion. RESULTS: The lower trapezius transfer generated, on average, 1.6 ± 0.2 nm more torque than the latissimus dorsi transfer (p < 0.001). The internal rotation/external rotation torques of all tendon transfers decreased as abduction increased (p < 0.01). At 0° elevation, reverse shoulder arthroplasty humeral component lateralization had a significant positive effect on tendon transfer torque at 60° internal rotation and external rotation (p < 0.01). DISCUSSION: Both the lower trapezius and the latissimus dorsi tendon transfers were effective in restoring active external rotation after reverse shoulder arthroplasty; however, the lower trapezius generated significantly more torque. Additionally, the pectoralis major transfer was effective in restoring active internal rotation. All tendon transfers were optimized with greater humeral component lateralization.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".