Surgical repair <i>versus</i> conservative treatment and subacromial decompression for the treatment of rotator cuff tears
Bibliographic record
Abstract
Aims The purpose of this study was to compare the effectiveness of surgical repair to conservative treatment and subacromial decompression for the treatment of chronic/degenerative tears of the rotator cuff. Materials and Methods PubMed, Cochrane database, and Medline were searched for randomized controlled trials published until March 2018. Included studies were assessed for methodological quality, and data were extracted for statistical analysis. The systematic review was conducted following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Results Six studies were included. Surgical repair resulted in a statistically significantly better Constant–Murley Score (CMS) at one year compared with conservative treatment (mean difference 6.15; p = 0.002) and subacromial decompression alone (mean difference 5.81; p = 0.0004). In the conservatively treated group, 11.9% of patients eventually crossed over to surgical repair. Conclusion The results of this review show that surgical repair results in significantly improved outcomes when compared with either conservative treatment or subacromial decompression alone for degenerative rotator cuff tears in older patients. However, the magnitude of the difference in outcomes between surgery and conservative treatment may be small and the ‘success rate’ of conservative treatment may be high, allowing surgeons to be judicious in choosing those patients who are most likely to benefit from surgery. Cite this article: Bone Joint J 2019;101-B:1100–1106.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".