Ovarian reserve after salpingectomy: a systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract Introduction Although there has been a growing concern over the possible damaging effect of salpingectomy on ovarian reserve, this issue remains uncertain. The purpose of this meta‐analysis was to test the hypothesis that salpingectomy may compromise ovarian reserve. Material and methods A detailed search was conducted using MEDLINE, Embase, Dynamed Plus, ScienceDirect, TRIP database and the Cochrane Library from January 2000 to November 2016. All cohort, cross‐sectional and randomized controlled studies investigating changes in circulating anti‐Müllerian hormone (AMH) after salpingectomy were considered. Thirty‐seven studies were identified, of which eight were eligible. Data were extracted and entered into RevMan software for calculation of the weighted mean difference (WMD) and 95% CI. Two groups of studies were analyzed separately: group 1 (six studies, n = 464) comparing data before and after salpingectomy and group 2 (two studies) comparing data in women who have undergone salpingectomy (n = 169) vs. healthy controls (n = 154). Results Pooled results of group 1 studies showed no statistically significant change in serum AMH concentration after salpingectomy (WMD, −0.10 ng/mL; 95% CI −0.19 to 0.00, I2 = 0%). Similarly, meta‐analysis of group 2 showed no statistically significant difference in serum AMH concentration between salpingectomy group and controls (WMD, −0.11 ng/mL; 95% CI −0.37 to 0.14, I2 = 77%). Subgroup analyses based on laterality of surgery, type of AMH kit and participants’ age (<40 years) still showed no statistically significant changes in circulating AMH. Conclusion Salpingectomy does not seem to compromise ovarian reserve in the short‐term. However, the long‐term effect of salpingectomy on ovarian reserve remains uncertain.
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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 | 0.014 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.033 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".