Repair of Full‐Thickness Rotator Cuff Tears in Patients Aged Younger Than 55 Years
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to conduct a systematic review of the available evidence regarding clinical outcomes after open or arthroscopic repair of full-thickness rotator cuff tears in young patients. METHODS: Medline, PubMed, and Embase were reviewed to find all studies examining full-thickness rotator cuff repairs in patients aged younger than 55 years and with a minimum of 1 year of follow-up. RESULTS: We found 7 studies that met the inclusion criteria. The mean patient age was 41.7 years (range, 16.2 to 54 years), and the mean time from injury was 66.1 months. Eighty-one percent of the included patients had a traumatic tear. The rotator cuff repair was supplemented by acromioplasty in 96.6% of patients, distal clavicle resection in 34.6%, and biceps tenodesis in 16.1%. Postoperative American Shoulder and Elbow Surgeons Standardized Shoulder Assessment was the most commonly reported outcome score, with a mean postoperative score of 82.0 (4 studies). Improvement was shown in all studies that reported on postoperative strength. All studies that assessed pain showed an improvement in the postoperative setting. Overall, 82% of the shoulders had satisfactory results. CONCLUSIONS: Full-thickness rotator cuff tears in patients aged younger than 55 years are mostly traumatic in origin and respond well to open and arthroscopic rotator cuff repair, as shown by good patient-reported outcomes, significant pain relief, improvement in strength, and high satisfaction postoperatively. LEVEL OF EVIDENCE: Level IV, systematic review of 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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".