Selection of the optimal day for oocyte retrieval based on the diameter of the dominant follicle in hCG-primed in vitro maturation cycles
Bibliographic record
Abstract
BACKGROUND: The efficiency of in vitro maturation (IVM) techniques is suboptimal compared with controlled ovarian stimulation combined with IVF cycles, and studies are needed to identify factors that predispose IVM cycles to success or failure. We compared the outcome of IVM cycles with different dominant follicle (DF) size at oocyte retrieval following hCG priming. METHODS: IVM was performed in 160 patients with polycystic ovaries (171 cycles). We administered 10,000 IU hCG s.c. 35-38 h before oocyte collection when endometrial thickness reached at least 6 mm. IVM cycles were retrospectively analyzed according to DF diameter as follows; Group 1: DF diameter 14 mm. RESULTS A positive correlation was observed between DF size and number of in vivo matured oocytes collected (Group 1, 2 and 3 = 6.9, 10.6 and 15.1%, respectively). The rates of IVM, fertilization and embryo development were similar among the sibling immature oocytes collected from the three groups. However, clinical pregnancy rate in Group 2 (40.3%) was higher than Group 3 (17.1%) (P < 0.05). Moreover, implantation rates in Groups 1 (13.6%) and 2 (14.3%) were higher than Group 3 (4.9%) (P < 0.01). CONCLUSIONS: Our results suggest that oocyte collection in IVM cycles should be performed when the DF is 14 mm diameter or less. Sibling immature oocytes may be affected detrimentally if a DF >14 mm is present at oocyte collection.
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 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 | 0.004 |
| 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) | 0.000 | 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 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".