Laparoscopic salpingectomy for women with hydrosalpinges enhances the success of IVF: a Cochrane review
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to determine whether surgical intervention is effective for women with tubal disease who are due to undergo treatment with IVF. METHODS: A systematic review employing the principles of the Cochrane Menstrual Disorders and Subfertility Group was undertaken. Three randomized controlled trials were included, the population of women in all three studies having hydrosalpinges. RESULTS: The odds of pregnancy [odds ratio (OR) = 1.75, 95% confidence interval (CI) 1.07-2.86] and of ongoing pregnancy and live birth (OR = 2.13, 95% CI 1.24-3.65) were increased with laparoscopic salpingectomy for hydrosalpinges prior to IVF. There were no significant differences in the odds of embryo implantation (OR = 1.34, 95% CI 0.87-2.05), ectopic pregnancy (OR = 0.42, 95% CI 0.08-2.14), miscarriage (OR = 0.49, 95% CI 0.16-1.52) or treatment complications (OR = 5.80, 95% CI 0.35-96.79). No data were available concerning the odds of multiple pregnancy or the proportion of IVF cycles resulting in embryo transfer. CONCLUSION: Laparoscopic salpingectomy should be considered for all women with hydrosalpinges due to undergo IVF; further research is required to assess other pre-IVF surgical interventions (such as needle aspiration of hydrosalpinx fluid, laparoscopic proximal tubal occlusion and laparoscopic salpingostomy) for women with hydrosalpinges.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".