Patient gender and rotator cuff surgery: are there differences in outcome?
Bibliographic record
Abstract
BACKGROUND: Although rotator cuff syndrome is common and extensively studied from the perspective of producing healed tendons, influence of gender on patient-reported outcomes is less well examined. As activity and role demands may vary widely between men and women, clarity on whether gender is an important factor in outcome would enhance patient education and expectation management. Our purpose was to determine if differences exist in patient-reported outcomes between men and women undergoing rotator cuff surgery. METHODS: One hundred forty-eight participants (76 W:72 M) aged 35-75 undergoing surgery for unilateral symptomatic rotator cuff syndrome were followed for 12 months after surgery. Demographics, surgical data, and the Western Ontario Rotator Cuff (WORC) scores were collected. Surgery was performed by two fellowship-trained shoulder surgeons at a single site. RESULTS: There were no gender-based differences in overall WORC score or subcategory scores by 12 months post-op. Pain scores were similar at all time points in men and women. Women were more likely to have dominant-arm surgery and had smaller rotator cuff tears than men. Complication rates were low, and satisfaction was high in both groups. CONCLUSION: Patient gender doesn't appear to exert an important effect on patient-reported rotator cuff outcomes in this prospective cohort. Further work examining other covariates as well as the qualitative experience of going through rotator cuff repair should provide greater insight into factors that influence patient-reported 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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".