Arthroscopic Repair for Chronic Massive Rotator Cuff Tears: A Systematic Review
Bibliographic record
Abstract
PURPOSE: To systematically review the available evidence for arthroscopic repair of chronic massive rotator cuff tears and identify patient demographics, pre- and post-operative functional limitations, reparability and repair techniques, and retear rates. METHODS: Medline, Embase, the Cochrane Database of Systematic Reviews, and the Cochrane Central Register of Controlled Trials were searched to identify all clinical papers describing arthroscopic repair of chronic massive rotator cuff tears. Papers were excluded if a definition of "massive" was not provided, if the definition of "massive" was considered inappropriate by agreement between the 2 reviewers, or if patients with smaller tears were also included in the study population. Study quality and clinical outcome data were pooled and summarized. RESULTS: There were 18 papers that met the eligibility criteria; they involved 954 patients with a mean age of 63 (range, 37 to 87), 48% of whom were female. There were 5 prospective and 13 retrospective study designs. The overall study quality was poor according to the Modified Coleman Methodology Score. Of the 954 repairs, 81% were complete repairs and 19% were partial repairs. The follow-up range was between 33 and 52 months, and the mean duration between symptom onset and surgery was 24 months. Single-row repairs were performed in 56% or patients, and double-row repairs were performed in 44%. A pooled analysis demonstrated an improvement in visual analog scale from 5.9 to 1.7, active range of motion from 125° to 169°, and the Constant-Murley score from 49 to 74. The pooled retear rate was 79%. CONCLUSIONS: Arthroscopic repair of chronic massive rotator cuff tears is associated with complete repair in the majority of cases and consistently improves pain, range of motion, and functional outcome scores; however, the retear rate is high. Existing research on massive rotator cuff repair is limited to poor- to fair-quality studies. LEVEL OF EVIDENCE: Level IV, systematic review including Level IV 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 | 0.008 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.006 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 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".