In vitro fertilization cycles stimulated with follitropin delta result in similar embryo development and quality when compared with cycles stimulated with follitropin alfa or follitropin beta
Bibliographic record
Abstract
OBJECTIVE: To study the impact of follitropin delta for ovarian stimulation on embryo development and quality compared with that of follitropin alfa or beta in in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) cycles. DESIGN: Retrospective cohort study. SETTING: University-affiliated, hospital-based fertility clinic. PATIENTS: A total of 403 IVF/ICSI cycles were conducted from September 1, 2018 to December 31, 2019. Cycles were grouped on the basis of stimulation with follitropin delta vs. follitropin alfa or beta. INTERVENTIONS: None. MAIN OUTCOME MEASURES: Embryo parameters and clinical pregnancy and implantation rates. RESULTS: Ovarian stimulation using follitropin delta resulted in no statistically significant difference in day 3 embryo quality between the control group and follitropin delta group (median 0.50 vs. 0.54 for good quality embryos and median 0.25 vs. 0.20 for intermediate quality embryos). Although on initial analysis there was a lower proportion of good quality blastocysts in the follitropin delta group than in the control group (0.11 vs. 0.22), this difference was no longer present when day 3 after fertilization vitrification and transfer cycles were excluded (0.26 vs. 0.33 follitropin delta vs. control). The clinical pregnancy rates and clinical implantation rates were similar in both groups in fresh transfer cycles. CONCLUSIONS: Stimulation with follitropin delta in IVF/ICSI cycles resulted in similar embryo development and pregnancy rates compared with those of stimulation with follitropin alfa or beta.
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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 | 0.003 |
| 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) | 0.003 | 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".