Pretreatment with a gonadotropin-releasing hormone agonist and an aromatase inhibitor may improve outcomes in in vitro fertilization cycles of women with stage I–II endometriosis
Bibliographic record
Abstract
OBJECTIVE: To determine whether 2 months of pretreatment with 5 mg of letrozole daily plus leuprolide acetate at 3.75 mg monthly in women with laparoscopically confirmed American Society of Reproductive Medicine stage I-II endometriosis improves in vitro fertilization (IVF) outcomes. DESIGN: Prospective cohort study. SETTING: University-affiliated tertiary hospital. PATIENT(S): Women with laparoscopically confirmed endometriosis treated in the period from 2012 to 2016. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Primary outcomes: clinical pregnancy and live-birth rate; secondary outcomes: stimulation parameters and pregnancy. RESULT(S): A total of 68 patients were included in the final analysis. Thirty-six women received a gonadotropin-releasing hormone (GnRH) agonist and an aromatase inhibitor (AI), and 32 women received a GnRH agonist alone. The women did not differ in mean age, antral follicle count, basal serum level of follicle-stimulating hormone, or previous pregnancies. The stimulation parameters were similar between both groups: gonadotropin dose, number of collected oocytes, number of blastocysts. All women underwent a single blastocyst transfer. The grade of embryos transferred did not differ. Clinical pregnancy (24 [66.7%] vs. 13 [40.6%]) and live-birth (22 [61.1%] vs 10 [31.3%]) rates improved with aromatase inhibitor added to the GnRH agonist treatment versus a GnRH agonist alone. CONCLUSION(S): In this study, we present the first comparison in the medical literature comparing IVF outcomes in women with minimal and mild endometriosis pretreated with a GnRH agonist with or without an AI. This prospective cohort study suggests that combining these two treatment modalities which work at different sites may improve pregnancy outcomes with IVF treatment.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".