Arthroscopic rotator cuff repair: patients with physically demanding work have significantly worse time to return to work, level of employment, and job loss
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to determine the results of arthroscopic rotator cuff repair (ARCR) in terms of return to work (RTW). METHODS: Inclusion criteria were working patients who underwent ARCR for rotator cuff rupture at the study site between 2008 and 2020 and minimum 12 months of follow-up. Patients were stratified based on the physical demand of their work according to the Canadian Classification and Dictionary of Occupations. The primary outcomes were time to RTW, level of employment (LoE), change of tasks, and work loss. Secondary outcomes included the return to sports activities, EQ-VAS, EQ-5D-5L, DASH, and Oxford Shoulder Score. RESULTS: Three-hundred and eighty-three patients were enrolled; at the follow-up evaluation, fifty-three patients (13.8%) lost their job, with a percentage of 34.4% (eleven patients) in the heavy-work category, and five patients (1.3%) chose early retirement. Other twenty-six patients (6.8%) had to lower their level of employment, and twenty patients (5.2%) changing their tasks, with 279 patients (72.9%) returning to their previous work activity. RTW was obtained at a mean time of 4.7 ± 4.6 months, ranging from 3.8 ± 3.1 months in the sedentary work vs 5.8 ± 2.8 months in the very heavy-work category (p = 0.015). The mean EQ-VAS score was 77.3 ± 18 points, the mean Oxford Shoulder Score was 43.4 ± 7.2 points, and the mean DASH score was 9.9 ± 14.5 points; 75.3% returned to their previous level of sport activity. CONCLUSIONS: The success of ARCR in terms of RTW is not always complete and varies significantly based on the physical demand of the patient's job. Patients with physically demanding work have a significantly higher time to RTW, reduction of the LoE, and job loss rate, thus affecting the possibility to have a satisfactory return to their previous life. The findings are of clinical relevance since they can help the surgeons to give their patients reliable expectations and to correctly plan the post-operative management. LEVEL OF EVIDENCE: IV.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".