Gender Differences in Surgery for Work-Related Musculoskeletal Injury: A Population-Based Cohort Study
Bibliographic record
Abstract
OBJECTIVE: The objective of this study is to examine if women are less likely than men to receive surgery following work-related musculoskeletal injury in the Canadian province of British Columbia. METHODS: The study included 2,403 workers with work-related knee meniscal tear, thoracic/lumbar disc displacement or rotator cuff tear. Probability of surgery was compared by gender using Kaplan-Meier methods and Cox proportional hazards models. RESULTS: For each injury type, a smaller proportion of women received surgery compared to men (knee: 76% vs. 80%; shoulder: 13% vs. 36%; back: 13% vs. 19%). In adjusted models, compared to men, women were 0.87 (95% confidence interval [CI] [0.69, 1.09]), 0.35 (95% CI [0.25, 0.48]) and 0.54 (95% CI [0.31, 0.95]) times less likely to receive knee, shoulder or back surgery, respectively. CONCLUSIONS: Probability of surgery following work-related musculoskeletal injury was lower for women than for men. Strategies to ensure gender equitable delivery of surgical services by workers' compensation systems may be warranted, although further research is necessary to investigate determinants of the gender difference and the impact of elective orthopaedic surgery on occupational 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".