The influence of ovarian hyperstimulation drugs on morphometry and morphology of human oocytes in ICSI program
Bibliographic record
Abstract
OBJECTIVE: To compare the influences of controlled ovarian hyperstimulation (COH) drugs using recombinant follicular stimulating hormone (rFSH) versus human menopausal gonadotropins (hMG) on morphometry and morphology of MII oocytes in ICSI cycles. MATERIALS AND METHODS: In this prospective study, 363 MII oocytes from 50 ICSI cycles with male factor infertility were evaluated. The patients were divided into two groups according to the protocols of COH: I- rFSH and II- hMG. The immature oocytes were excluded from the study. All oocytes were categorized into four morphological groups of normal, and those with single, double, or multiple defects. The inclusive morphometrical criteria were: areas and diameters of oocyte, ooplasm, and zona pellucida (ZP). Also, circumferences of oocyte and ooplasm were assessed. RESULTS: The ZP area and ooplasm diameter for both normal and abnormal oocytes were significantly higher in group I (P: .05; P: .028, respectively) compared to group II (P: .023; P: .003, respectively). In abnormal oocytes, ooplasm diameter was higher in group I compared to group II. Furthermore, ooplasm area for abnormal oocytes was significantly higher in group I compared to group II. There was an increasing trend for number of mature oocytes, in abnormal oocytes, for group I (5.53 ± 3.1) in comparison with group II (4.4 ± 2.97; P = .25). The rate of oocytes with normal morphology was significantly higher in hMG, when compared to rFSH groups. CONCLUSION: Morphometrical parameters were increased in rFSH group, but the normal morphology of oocytes were significantly enhanced in hMG group. Treatment with proper dosage of ovulation induction drugs may enhance the number of normal sized oocytes.
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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 | 0.000 | 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".