Comparison of pregnancy outcomes in natural cycle IVF/M treatment with or without mature oocytes retrieved at time of egg collection
Bibliographic record
Abstract
The objective of this study is to compare the pregnancy and live birth rates of a natural cycle in vitro fertilization (IVF) combined with in vitro maturation (IVM) treatment (natural cycle IVF/M) by the presence or absence of mature oocytes retrieved. Infertile women were divided into two groups: (A) patients with mature oocytes found at retrieval and (B) patients with only immature oocytes at retrieval. Patients of group A were further divided into three subgroups: (A1) mature oocytes retrieved from both the leading and the small follicles, (A2) mature oocytes retrieved from the leading follicles only, and (A3) mature oocytes retrieved from the small follicles only. Pregnancy and implantation rates were compared. The results indicate that the clinical pregnancy rates were 40.1% (126/314) and 34.5% (19/55) for groups A and B, respectively. There were no differences in pregnancy rates among the subgroups: A1=44.0% (66/150), A2=34.9% (30/86), and A3=38.5% (30/78). In addition there were no differences in implantation rates among the groups (16.2% =139/859, 15.0% =22/147, 16.8% =69/410, 14.7% =34/232, and 16.6% =36/217, respectively). However, the live birth and miscarriage rates were significantly different between the group A and group B (29.6% =93/314 vs. 16.4% =9/55 and 26.2% =32/126 vs. 52.6% =10/19, respectively). In conclusion, for natural cycle IVF/M treatment, although the clinical pregnancy rates are not different regarding the retrieval of mature oocytes or the time of the egg retrieval, the live birth rate is higher (P < 0.05) when the mature oocytes are obtained at the time of the egg retrieval.
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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 | 0.006 |
| 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".