Is Bony Morphology and Morphometry Associated With Degenerative Full‐Thickness Rotator Cuff Tears? A Systematic Review and Meta‐analysis
Bibliographic record
Abstract
PURPOSE: To scope the scientific literature and analyze the influence of bony risk factors for degenerative full-thickness primary rotator cuff tear. METHODS: A systematic review of databases PubMed, Scopus, EMBASE, and Cochrane Library was performed up to June 30, 2018. Meta-analysis was performed with mean difference (MD) or risk ratio for degenerative full-thickness rotator cuff injury, and when there were ≥3 studies for the considered potential risk factor. Methodologic quality was assessed using the Newcastle-Ottawa scale. RESULTS: We analyzed 34 studies comprising 5,916 shoulders (3,369 shoulders with rotator cuff tear and 2,546 controls) and identified 19 potential risk factors for degenerative full-thickness rotator cuff tears. There was moderate evidence that a higher critical shoulder angle (MD = 4.41, 95% confidence interval [CI] 3.43 to 5.39), higher acromion index (MD = 0.06, 95% CI 0.04 to 0.09), and lower lateral acromion angles (MD = -7.11, 95% CI -8.32 to -5.90) were associated with degenerative full-thickness rotator cuff tears compared with controls. Moderate evidence showed that a type III acromion significantly increases the risk for full-thickness degenerative rotator cuff tear (risk ratio = 2.26, 95% CI 1.38 to 3.70). CONCLUSION: There is moderate evidence that larger critical shoulder angle, higher acromion index, lower lateral acromion angles, and a type III acromion are significantly associated with degenerative full-thickness rotator cuff tears. Other potential risk factors identified showed insufficient evidence. 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 | 0.012 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.028 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 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".