Avoidable bilateral salpingo-oophorectomy at hysterectomy: a large retrospective study
Bibliographic record
Abstract
OBJECTIVES: Evaluate the proportion of justified bilateral salpingo-oophorectomy (BSO) at hysterectomy, based on pathologic diagnosis, and determine prevalence of avoidable BSO based on pre- and intraoperative considerations and pathologic diagnosis. METHODS: Retrospective review of hysterectomies at seven Ontario, Canada hospitals from 2016 to 2019. Surgeries completed by oncologists or for invasive placentation were excluded. Patient, case, and surgeon characteristics were recorded along with pathologic diagnoses. Avoidable BSO criteria were: preoperative diagnosis of cervical dysplasia or benign diagnosis other than endometriosis, gender dysphoria, risk reduction or premenstrual dysphoric disorder; age < 51 years; absence of intraoperative endometriosis and adhesions; unjustified pathology (where "justified" pathology was endometriosis or (pre)malignant diagnosis except for cervical dysplasia). Patients with avoidable BSO were compared to those having at least one criterion for BSO. Binary logistic regression identified factors most strongly associated with avoidable BSO. RESULTS: Four thousand one hundred ninety-one hysterectomies were completed with 1,422 (33.9%) patients having concomitant BSO. Pathologic diagnosis justified BSO in most patients (1,035/1,422, 72.8%) with endometrial cancer being most common (439/1,422, 30.9%). When preoperative characteristics, intraoperative findings, and pathologic diagnoses were considered, 79 of 1,422 (5.6%) BSOs were avoidable. Compared to cases with at least one criterion for BSO, avoidable BSOs were more frequently completed by generalists (OR 1.80, 95% CI 1.10-2.99, P = 0.021), for preoperative diagnoses of abnormal uterine bleeding/menorrhagia (OR 3.82, 95% CI 2.35-6.30, P = 0.001) and fibroids (OR 4.25, 95% CI 2.63-6.92, P < 0.001). CONCLUSION: Pathologic diagnosis justified most BSOs at hysterectomy. BSO was avoidable in 5.6% of patients, underscoring the need to standardize practice of BSO.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".