Short‐term relugolix use for rapidly growing uterine fibroids before uterus‐preserving surgery in women seeking to conceive: Two case reports
Bibliographic record
Abstract
Large uterine fibroids that grow rapidly over a short period should be differentiated from uterine leiomyosarcoma, and their treatment remains controversial in women seeking to conceive. Here, we report two cases of uterine fibroids treated with short-term relugolix administration followed by myomectomy. Needle biopsy specimens obtained before relugolix administration showed no malignancy, and significant tumor shrinkage was observed following treatment. Both patients subsequently underwent myomectomy. One patient achieved a live birth 14 months after myomectomy, whereas the other experienced improvement in severe anemia, allowing her to prepare for pregnancy. Histological examination after relugolix administration revealed atrophic changes in spindle cells within the fibroids, characterized by nuclear crowding and decreased immunoreactivity for desmin and α-smooth muscle actin. The significant fibroid shrinkage observed after the short-term administration of relugolix provided a rationale for myomectomy, improved anemia, and facilitated appropriate uterine reconstruction, ensuring structural integrity for future pregnancies in women of reproductive age.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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".