Uterine Fibroid Embolization in Patient With Symptomatic Uterine Leiomyomas in Uterine Didelphys
Bibliographic record
Abstract
Uterine didelphys is a rare congenital anomaly resulting from compete failure of Mullerian duct fusion, occurring in 0.5-5% of women. Its coexistence with uterine leiomyomas is extremely uncommon, with an estimated prevalence of 0.0026%. Surgical treatments such as hysterectomy or myomectomy are commonly used for uterine fibroid treatments. However, Uterine fibroid embolization (UFE) is a minimally invasive, fertility-sparing alternative that remains underutilized. We report a case of a 41-year-old Vietnamese woman who presented with abnormal uterine bleeding and pelvic pain and was found to have uterine didelphys with bilateral symptomatic fibroids. Magnetic resonance imaging (MRI) confirmed large fibroids in both uteri, with the largest measuring 14 × 11 × 1cm on the left side. Following consultation with the patient, and given her preference for a non-surgical option, she underwent successful UFE via selective embolization of both uterine arteries using Terumo (Terumo Company, Tokyo, Japan) Hydropearls 200 - 400 µm microspheres. Post-angiographic embolization of the uterine fibroids confirmed complete occlusion of the fibroid vascular supply, and a post-embolization MRI is scheduled for 3 months after the procedure. The patient tolerated the procedure well with no complications. This case highlights the effectiveness of UFE in a patient with the rare co-occurrence of uterine didelphys and symptomatic leiomyomas. UFE offers a safe, minimally invasive alternative to surgery even in complex cases, and should be more widely considered in eligible patients.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".