Treatment of Endometriosis with the GnRHa Deslorelin and Add-Back Estradiol and Supplementary Testosterone
Bibliographic record
Abstract
BACKGROUND: This randomized, multicenter, open-label clinical trial was intended to generate pilot data on the efficacy and safety of the gonadotropin-releasing hormone agonist (GnRHa) deslorelin (D) with low-dose estradiol ± testosterone (E2 ± T) add-back for endometriosis-related pelvic pain. METHODS: Women with pelvic pain and laparoscopically confirmed endometriosis were treated with a six-month course of daily intranasal D with concurrent administration of either transdermal E2, intranasal E2, or intranasal E2 + T. Efficacy data included evaluation of dyspareunia, dysmenorrhea, pelvic pain, tenderness, and induration. Cognition and quality of life were also assessed. Safety parameters included assessment of endometrial hyperplasia, bone mineral density (BMD), and hot flashes. RESULTS: Endometriosis symptoms and signs scores decreased in all treatment arms from a baseline average of 7.4 to 2.5 after 3 months of treatment and 3.4 after 6 months. BMD changes and incidence of hot flashes were minimal, and no endometrial hyperplasia was observed. Patient-reported outcomes showed significant improvement across multiple domains. CONCLUSIONS: Daily intranasal D with low dose E2 ± T add-back resulted in significant reduction in severity of endometriosis symptoms and signs with few safety signals and minimal hypoestrogenic symptoms that would be expected with the use of a GnRHa alone.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".