Return to Sport After Coracoid Transfer in Athletes With Anterior Shoulder Instability: A Systematic Review
Bibliographic record
Abstract
CONTEXT: Recurrent shoulder instability in young athletes can lead to a spectrum of soft tissue and bony lesions that can be bothersome and/or disabling. Coracoid transfer is a treatment option for athletes with recurrent instability. OBJECTIVE: To report the rate of return to sport for athletes after coracoid transfer. DATA SOURCES: An electronic search of the literature was performed using the PubMed (MEDLINE) and Cochrane Databases (1966-2018). STUDY SELECTION: Studies were included if they evaluated return to sport after treatment with coracoid transfer at a minimum 1-year follow-up. STUDY DESIGN: Systematic review. LEVEL OF EVIDENCE: Level 4. DATA EXTRACTION: Data were extracted by 2 authors and included study design, level of evidence, patient demographics (number, age, sex), procedure performed, duration of clinical follow-up, rate of return to sport, patient-reported outcome measures, reoperations, and complications. RESULTS: Fourteen studies met the inclusion criteria. The rate of return to sport at any level ranged from 80% to 100% in all but 1 study (38%), and the rate of return to the previous level of play ranged from 56% to 95% in all but 1 study (16%). Patients returned to sport at an average of 3.2 to 8.1 months. The average patient-reported outcome scores ranged from 78% to 94% (Rowe), 223.6 to 534.3 (Western Ontario Shoulder Instability Index), and 75% to 90% (subjective shoulder value). The rate of postoperative dislocation ranged from 0% to 14%, and the reoperation rate ranged from 1.4% to 13%. CONCLUSION: There was a high early rate of return to sport in patients who underwent coracoid transfer for anterior shoulder instability, although patients did not reliably return to the same level of play. The procedure had very favorable outcomes for treatment of instability, with low rates of recurrent dislocation and reoperation.
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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 | 0.005 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".