Is arthroscopic repair superior to biceps tenotomy and tenodesis for type II SLAP lesions? A meta-analysis of RCTs and observational studies
Bibliographic record
Abstract
OBJECTIVE: Labral repair and biceps tenotomy and tenodesis are routine operations for type II superior labrum anterior posterior (SLAP) lesion of the shoulder, but evidence of their superiority is lacking. We conducted this systematic review and meta-analysis to compare the clinical outcomes of arthroscopic repair versus biceps tenotomy and tenodesis intervention. METHODS: The eight studies were acquired from PubMed, Medline, Embase, CNKI, and Cochrane Library. The data were extracted by two of the coauthors independently and were analyzed by RevMan 5.3. Mean differences (MDs), odds ratios (ORs), and 95% confidence intervals (CIs) were calculated. Cochrane Collaboration's Risk of Bias Tool and Newcastle-Ottawa Scale were used to assess risk of bias. RESULTS: Eight studies including two randomized controlled trials (RCTs) and six observational studies were assessed. The methodological quality of the trials ranged from low to moderate. The pooled results of UCLA score, SST score, and complications showed that the differences were not statistically significant between the two interventions. The difference of ASES score and satisfaction rate was statistically significant between arthroscopic repair and biceps tenotomy and tenodesis intervention, and arthroscopic biceps tenotomy and tenodesis treatment was more effective. Sensitivity analysis proved the stability of the pooled results, and there were too less included articles to verify the publication bias. CONCLUSIONS: Both arthroscopic repair and biceps tenotomy and tenodesis interventions had benefits in type II SLAP lesions. Arthroscopic biceps tenotomy and tenodesis treatment provides better clinical outcome in ASES score and satisfaction rate and comparable complications compared with arthroscopic repair treatment. In view of the heterogeneity and confounding factors, whether these conclusions are applicable should be further determined in future 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 | 0.035 | 0.070 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.056 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".