Oophorectomy or ovarian conservation at the time of hysterectomy for benign disease
Bibliographic record
Abstract
Key content Bilateral salpingo‐oophorectomy is indicated for patients with suspected or confirmed gynaecological malignancy. Risk reduction surgery is indicated in patients with a significant family history or a genetic predisposition to developing breast or ovarian cancer. Bilateral salpingectomy with ovarian conservation reduces the risk of ovarian cancer, whilst preserving ovarian function. Oophorectomy prior to the menopause is associated with increased all‐cause mortality and significant menopause related morbidity. Conservative measures such as weight loss, family planning and lifestyle advice could reduce the overall lifetime risk of ovarian cancer. Learning objectives To understand the rationale of the decision‐making process for bilateral salpingo‐oophorectomy or bilateral salpingectomy with ovarian conversation at the time of hysterectomy for benign disease. To understand the risk–benefit balance of performing oophorectomy in the context of risk reduction of high‐risk patients compared with patients with no genetic predisposition or family history. To consider conservative risk reduction measures that do not involve oophorectomy. Ethical issues In the absence of family history or genetic predisposition to ovarian or breast cancer, is it ethical to perform routine oophorectomy in perimenopausal or even postmenopausal women? Is it ethical to reduce the risk of ovarian cancer while increasing all‐cause mortality and menopause‐related morbidity? Is it ethical to offer bilateral salpingectomy as a female sterilisation procedure?
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.040 | 0.003 |
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".