Controversies in surgical management of anterior shoulder instability. State of the Art
Bibliographic record
Abstract
Arthroscopic Bankart repair (ABR) has been accepted as a standard procedure for anterior shoulder instability with a minimum or no glenoid bone loss and an on-track Hill-Sachs lesion if present. However, several controversies exist in the surgical treatment of anterior shoulder instability. This article will discuss some of these controversies in, "simple," dislocations (without bone loss) as well as, "complex," (with critical bone loss). Determining which patients will benefit from an arthroscopic procedure depends on multiple factors including age, activity level, adequate determination of bone loss, performed with feasible and reliable imaging techniques. In the absence of concomitant significant bony and soft tissue pathology, ABR alone can provide satisfactory clinical results on a long-term basis. Controversies, including whether to remove cartilage from the edge of the glenoid, knotted versus knotless anchors, and routine rotator interval closure, still exist. In cases with significant bone loss, several bone restoring procedures have been described, such as, the Latarjet procedure, iliac crest bone graft, arthroscopic anatomic glenoid reconstruction with a frozen distal tibial allograft, and fresh distal tibial allograft reconstruction. This article will address these controversies and provide guidance based on available published data.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".