Arthroscopic Bankart shoulder stabilization in athletes: return to sports and functional outcomes
Bibliographic record
Abstract
PURPOSE: The aim of this study was to evaluate return to sports after arthroscopic Bankart stabilization. METHODS: This is a retrospective study including all athletes aged <50 years who underwent arthroscopic stabilization in 2010 and 2011 (m, 36; f, 10; mean age 28.9 ± 8.1 years; follow-up 24.4 ± 7.7 months). Sixteen patients were practicing competitive sports and 30 recreational sports. Level and delay of return to sports, sports classification according to Allain, Western Ontario Shoulder Instability Index (WOSI) score, patient satisfaction, apprehension level and avoidance behaviour were noted. RESULTS: 95.7 % returned to the same level after an average of 9.8 ± 5.4 months. Sports level was unchanged or better in 82.6 %, lower in 8.7, and 4.5 % changed sport because of their shoulder. Patients with more than 10 dislocations returned to sports and to their preoperative level later than patients with <10. Male athletes returned to preoperative sports levels faster than female athletes (p < 0.001). The WOSI score and also its item "sports" were worse in those who had not returned (p = 0.0002 and 0.006, respectively). Satisfaction correlated with the WOSI score (p = 0.0004) while 93.3 % were satisfied/very satisfied. The decrease in the apprehension level was significant (p < 0.00001). 36.9 % still experienced avoidance behaviour. CONCLUSIONS: Most athletes resumed their main sport often at the same level, but the threshold of 10 dislocations should be considered a risk factor for longer return to sports at any level. The WOSI score is a valuable outcome score after Bankart stabilization. Postoperative avoidance should be distinguished from apprehension. LEVEL OF EVIDENCE: IV.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".