Anterior Capsule Augmentation and Posterior Glenohumeral Capsular Reconstruction With Human Dermal Allograft for Multidirectional Shoulder Instability
Bibliographic record
Abstract
Recurrent multidirectional shoulder instability is a common clinical presentation in certain demographics and sporting groups. One such demographic is patients with connective tissue disorders (CTD) such as Ehlers-Danlos syndrome (EDS), in whom shoulder pathologies are exacerbated owing to ligamentous laxity. Features of this laxity can present as both anterior and posterior shoulder instability, which are problematic sources of shoulder pain. Many patients with these injuries require surgical anterior and/or posterior glenohumeral reconstruction. Surgical reconstruction for posterior capsular defects can be challenging and has higher failure rates compared with anterior capsular reconstruction methods. Management can be especially difficult for patients with CTDs, and there is a requirement for the development of novel surgical techniques. Human acellular dermal allografts have been found to be particularly useful for patients with CTDs compared with other methods that use the patient's own tissue for the repair. This note and surgical video describe an all-arthroscopic technique for a combined anterior capsule augmentation and posterior glenohumeral capsular reconstruction, using a human acellular dermal allograft for EDS patients with multidirectional instability.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".