Impact of Uterine Artery Embolization on Subsequent Fertility Outcomes: A Meta-Analysis of 20 Years of Clinical Evidence
Bibliographic record
Abstract
Background: Uterine fibroids affect 70–80% of women by age 50, often impairing fertility through mechanical distortion and altered endometrial receptivity. Uterine artery embolization (UAE) is a minimally invasive alternative to surgery, though its impact on future fertility remains debated. This meta-analysis aimed to evaluate pregnancy rates, time to conception, and fertility-related complications following UAE in women with symptomatic fibroids. Methods: A systematic search was performed across PubMed/MEDLINE, Embase, Cochrane Library, Web of Science, and other databases (January 2005–March 2025) following PRISMA 2020 guidelines. Studies reporting fertility outcomes ≥ 6 months after UAE were included. Primary outcomes were pregnancy rates and time to conception. A random-effects meta-analysis was conducted using Review Manager 5.4. Study quality was assessed with the Newcastle–Ottawa Scale (observational studies) and the Cochrane Risk of Bias tool for randomized controlled trials (RCTs). Results: Thirty-three studies (4287 women) were included; 85.2% had follow-up. The pregnancy rate was 52.1% (95% CI: 46.8–57.4%), with a mean time to conception of 14.7 months. Pregnancy rates were highest in women < 30 years (67.8%) and lowest in those > 40 years (31.5%). Unilateral UAE had superior outcomes to bilateral (61.2% vs. 49.8%). Conclusions: UAE can preserve fertility in ~50% of selected patients, with better outcomes in younger women. Early intervention is advised for fertility preservation.
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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 | 0.017 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.061 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".