Practice Patterns and Long-term Health Outcomes of Bilateral Salpingo-Oophorectomy at Benign Hysterectomy
Bibliographic record
Abstract
Background: Bilateral salpingo-oophorectomy (BSO) is offered at the time of benign hysterectomy to prevent ovarian cancer later in life. However, BSO results in the cessation of ovarian hormone production and may be harmful to long-term health. If BSO is associated with adverse outcomes, then understanding variation in surgeon practice will help identify targets for knowledge translation and quality improvement. Methods: We performed three population-based observational studies of women undergoing benign hysterectomy in Ontario, Canada, using linked administrative databases held at ICES. We used mixed logistic regression modelling to describe between-surgeon variation in BSO; overlap propensity score weighted survival modelling to determine whether BSO was associated with all-cause and cause-specific death; and inverse probability of treatment weighted survival modelling to quantify the risk reduction in ovarian cancer associated with BSO. Results: Rates of BSO at benign hysterectomy varied markedly between surgeons even after adjusting for patient case-mix, and the surgeon providing care was one of the strongest factors influencing whether patients underwent BSO (median odds ratio 2.10, 2.49, 2.84, 2.00 in women
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".