Does an Increased Critical Shoulder Angle Affect Re‐tear Rates and Clinical Outcomes Following Primary Rotator Cuff Repair? A Systematic Review
Bibliographic record
Abstract
Purpose To determine if an increased critical shoulder angle (CSA) predisposes patients to higher re‐tear rates and worse clinical outcomes after rotator cuff (RC) repair. Methods A comprehensive search of the PubMed, MEDLINE, and EMBASE databases was performed in October 2018 for English‐language studies pertaining to RC repair and an increased CSA in accordance with Preferred Reported Items for Systematic Reviews and Meta‐analyses guidelines. Studies of all levels of evidence were included provided that any outcomes, including pain, patient‐reported outcomes, and re‐tear rates, were reported. Results Of a group of 1126 studies that satisfied the initial search criteria, 6 studies were included in the final analysis, comprising data from 473 patients. Three comparative studies were assessed for an association between increased CSA and RC re‐tear rates. Among these 3 studies that compared RC re‐tear rate in patients with larger and smaller CSAs, 22 of 97 patients (23%) with a larger CSA had a RC re‐tear in comparison to 10 of 99 patients (10%) with a smaller CSA. All 3 studies demonstrated higher RC re‐tear rates in patients with larger CSAs (risk ratio, 2.39‐9.66, I 2 = 7%.) The mean CSA in those patients who did not have RC re‐tears ranged from 34.3° to 37°, and the mean CSA in those patients who had RC re‐tears ranged from 37° to 40°. Conclusion RC re‐tear rates were higher in patients with larger CSAs among comparative, nonrandomized studies. However, the heterogeneity of the relevant literature limits the strength of his observation. Based on the current literature, it remains unclear as to whether lateral acromioplasty affects clinical outcomes as a function of a reduced postoperative CSA. Level of Evidence Level IV, systematic review of Level II to 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 | 0.011 | 0.060 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.011 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 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".