Dual oocyte retrieval and embryo transfer in the same cycle for women with premature ovarian insufficiency
Bibliographic record
Abstract
OBJECTIVE: To compare dual oocyte retrieval with minimal ovarian stimulation and embryo transfer in the same menstrual cycle versus conventional ovarian stimulation among women with premature ovarian insufficiency (POI). METHODS: A retrospective study of 51 women with POI attending a reproductive center in Turkey between 2013 and 2015. Women with an ovarian follicle of 12 mm or larger early in the follicular phase who underwent oocyte retrieval followed by an immediate cycle of ovarian stimulation (group 1, n=14) were compared with those who received conventional ovarian stimulation (group 2, n=37). Both groups underwent subsequent ovarian stimulation cycles to obtain optimally two embryos for transfer. RESULTS: The groups had similar baseline parameters. Serum estradiol was higher in group 1 (P<0.001); total number of oocyte retrievals was higher in group 2 (P<0.001); and total number of oocytes retrieved was similar (P=0.192). Group 1 had more higher-quality embryos (P=0.031). There was a non-significant trend toward higher live birth rates in the dual trigger group (28% vs 8%, P=0.08). CONCLUSION: Rescuing growing follicles early in the follicular phase combined with subsequent ovarian stimulation and embryo transfer in the same cycle resulted in fewer oocyte retrieval cycles and might potentially improve reproductive outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".