Clinical Outcomes and Return to Sports After Arthroscopic Repair of Humeral Avulsion of the Glenohumeral Ligament: A Meta-Analysis
Bibliographic record
Abstract
This study aimed to evaluate the clinical outcomes and the frequency of return to sport after the arthroscopic repair of a humeral avulsion of the inferior glenohumeral ligament (HAGL) lesion. Web of Science, Scopus, and Medline via PubMed and OVID were searched to identify the relevant citations. Screening and data extraction were performed independently. The Comprehensive Meta-Analysis software was used for all statistical analyses (CMA; USA version 3.3.070). A total of 18 articles (n = 832 patients; of whom, 379 patients had HAGL) were included. The fixed-effect estimate showed that the percentage of patients who returned to their sports was 89.1% (95% CI = 85% to 92.2%). The mean duration to return was estimated to be 6.65 months (95% CI = 5.10 to 8.20). Postoperatively, the mean Western Ontario Shoulder Instability Index (WOSI), Oxford Shoulder Instability Score (OSIS), and Subjective Shoulder Value (SSV) scores were 88.60 (95% CI = 86.18 to 90.98), 15.02 (95% CI = 7.42 to 22.63), and 86.90 (95% CI = 80.79 to 93.00), respectively. The Rowe score improved significantly postoperatively with a mean difference (MD) of 54.47 (95% CI = 39.28 to 69.66). The University of California - Los Angeles (UCLA) shoulder score increased significantly post-arthroscopic repair (MD = 10.91, 95% CI = 10.07 to 11.76). The current evidence suggests that arthroscopic repair of HAGL lesions is associated with a high percentage of return to sports and improved Rowe score, WOSI, UCLA shoulder score, OSIS scale, and SSV score. The quality of the included studies is moderate; however, these findings are promising and call for further multicenter, prospective studies.
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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 | 0.012 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.046 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".