Outcomes for intra-substance free coracoid graft in patients with antero-inferior instability and glenoid bone loss in a population of high-risk athletes at a minimum follow-up of 2 years
Bibliographic record
Abstract
BACKGROUND: The aim of this retrospective case series study was to assess the outcomes of patients with recurrent anterior shoulder instability with antero-inferior glenoid bone loss treated with a specific open stabilization technique using intra-substance coracoid bone-grafting and Bankart repair. METHODS: Over a 4-year period, 34 shoulders in all male patients of mean age 21 years were stabilized with this technique. Pre- and postoperative function, motion and stability were assessed as part of Rowe stability scoring, and American Shoulder and Elbow Surgeons (ASES) and Oxford Instability were recorded, with at least 2 years of follow-up in all patients. Union of the graft was determined by post-operative computed tomography (CT) of the affected shoulder. RESULTS: For all cases, two redislocations (5.9%) and two subluxations occurred when continuing high-risk sport after 2 years. Post-operative scores [median, mean (SD): Rowe 77.5, 77.2 (19.5); ASES 94.2, 92 (7.7); Oxford 43, 41.2 (6)]. CT scans on 28 shoulders at a mean of 4.5 months after surgery showed non-union in three cases (10%). CONCLUSIONS: These results demonstrate a high rate of success in cases of glenoid bone loss in the young contact athlete with recurrent instability treated with open stabilization and bone grafting.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".