Time to surgery in acute rotator cuff tear
Bibliographic record
Abstract
AIMS: We performed a systematic review of the literature to determine whether earlier surgical repair of acute rotator cuff tear (ARCT) leads to superior post-operative clinical outcomes. METHODS: The MEDLINE, Embase, CINAHL, Web of Science, Cochrane Libraries, controlled-trials.com and clinicaltrials.gov databases were searched using the terms: 'rotator cuff', or 'supraspinatus', or 'infraspinatus', or 'teres minor', or 'subscapularis' AND 'surgery' or 'repair'. This gave a total of 15 833 articles. After deletion of duplicates and the review of abstracts and full texts by two independent assessors, 15 studies reporting time to surgery for ARCT repair were included. Studies were grouped based on time to surgery < 3 months (group A, seven studies), or > 3 months (group B, eight studies). Weighted means were calculated and compared using Student's t-test. RESULTS: Group B had a significantly higher pre-operative Constant score (CS) (p < 0.001), range of movement in external rotation (p = 0.003) and abduction (p < 0.001) compared with group A. Both groups showed clinical improvement with surgical repair; group A had a significantly improved Constant score, University of California, Los Angeles (UCLA) shoulder score, abduction and elevation post-operatively (all p < 0.001). Group B had significantly improved Constant score (p < 0.001) and external rotation (p < 0.001) post-operatively. The mean Constant score improved by 33.5 for group A and by 27.5 for group B. CONCLUSION: These findings should be interpreted with caution due to limitations and bias inherent to case-series. We suggest a trend that earlier time to surgery may be linked to better Constant score, and active range of movement in abduction and elevation. Additional prospective studies are required.
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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 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| 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".