Laboratory and embryological aspects of hCG-primed in vitro maturation cycles for patients with polycystic ovaries
Bibliographic record
Abstract
BACKGROUND: In this review, recent advances in the laboratory as well as embryological aspects of hCG priming in vitro maturation (IVM) cycles are described. METHODS: This report is based on publications from literature searches and the authors' experience. RESULTS: In IVM cycles, priming with hCG permits the recovery of a certain number of oocytes with an expanding/dispersed cumulus pattern which facilitates its identification within follicular fluid as compared with non-primed IVM cycles. The immature oocytes with dispersed cumulus cells (CC) at collection have high IVM rates and embryo development potentials. Moreover, a few in vivo matured oocytes with dispersed CC can be obtained, and these have produced good quality embryos. hCG can be given to patients when a dominant follicle reaches 10-12 mm to avoid negative effects on the sibling immature oocytes. ICSI should be performed at least 1 h after the first polar body extrusion. Embryo transfer time depends on quantity and quality of the embryos produced after IVM. Compared with slow freezing, vitrification is a more efficient method for freezing the embryos produced from IVM. CONCLUSIONS: The data from the meta-analyses suggests that the effect on clinical outcome of gonadotrophin priming of IVM still needs to be studied. In order to improve the IVM programs, it is essential to define not only the clinical aspects but also the laboratory and embryological aspects.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".