Efficacy of Ovarian Artery Embolization for Uterine Fibroids
Bibliographic record
Abstract
PURPOSE: The objective of the study was to assess the efficacy of ovarian artery embolization (OAE) treatment for symptomatic uterine leiomyomas. METHODS: A retrospective review of 17 patients who underwent OAE in conjunction with uterine artery embolization in a 6-year period (2006-2012) was performed. Ten patients had previous failed embolization, while 7 had not received any embolization therapy before. Percent uterine volume change, percent dominant fibroid volume change, and percent dominant fibroid infarction were assessed with magnetic resonance (MR) imaging. Resolution of menorrhagia, dysmenorrhea/pain, and bulk and/or pressure symptoms including urinary frequency were evaluated clinically. Change in menopausal state was also an outcome of interest. RESULTS: Mean MR imaging follow-up was performed 3 months post-OAE. MR images showed complete infarction in the majority of cases (64.7%; n = 11), with infarction rates of 90%-100% in 3 cases, 1 case with 30%-50% infarction, and 2 cases with 0%-10% infarction. Average uterine size reduction on MR was 32.3% (95% confidence interval [CI]: 22.5%-42.2%; P < .001). The average size reduction for the dominant fibroid was 42.4% (95% CI: 27.7%-57.0%; P = .01). The mean time to final follow-up visit was 11 months. At this point complete symptom resolution (menorrhagia, dysmenorrhea and bulk-related) was achieved in 82.4% (n = 14) of cases. At the final follow-up 11.8% (n = 2) of cases reported menopause. CONCLUSIONS: We observed OAE to be an effective and safe adjunct to uterine artery embolization when hypertrophic ovarian artery(ies) require intervention. However, incomplete fibroid infarction of 23% remains a concern with a potential for long-term treatment failure. In addition, long-term effect on ovarian function is uncertain.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".