Return to Work After Primary Rotator Cuff Repair: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
BACKGROUND: Rotator cuff tears are a prevalent pathology in injured workers, causing significant economic ramifications and time away from work. To date, published articles on work outcomes after rotator cuff repair have not been cumulatively assessed and analyzed. PURPOSE: To systematically review reports on return to work after rotator cuff repair and perform a meta-analysis on factors associated with improved work outcomes. STUDY DESIGN: Systematic review and meta-analysis; Level of evidence, 4. METHODS: A systematic review of return-to-work investigations was performed using PubMed, Embase, and the Cochrane Database of Systematic Reviews in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Individual studies reporting rates of return to previous work with level of evidence 1 to 4 were independently screened by 2 authors for inclusion, and study quality was assessed using the Methodologic Index for Non-randomized Studies and Newcastle-Ottawa Scale. Work outcome data were synthesized and analyzed using random effects modeling to identify differences in rates of return to previous work as a function of operative technique, work intensity, and workers' compensation status. RESULTS: = .089). All shoulder pain and functional outcome assessments demonstrated significant improvements at final follow-up when compared with baseline across all investigations. CONCLUSION: The majority of injured workers undergoing rotator cuff repair return to previous work at approximately 8 months after surgery. Despite this, >35% of patients are unable to return to their previous work level after their repair procedure. Similar rates of return to work can be anticipated regardless of workers' compensation status and operative technique, while patients in occupations with higher physical intensity experience inferior work outcomes.
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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 | 0.021 | 0.049 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.055 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".