Oocyte and zygote development potential in minimal stimulation, natural cycle and conventionally stimulated IVF: an international multi-centre retrospective cohort study
Bibliographic record
Abstract
PURPOSE: The aim of this research is to assess the development potential of oocytes and zygotes obtained from Natural cycle IVF (NC-IVF), different minimal stimulation IVF (Min stim-IVF) and conventionally stimulated IVF (cIVF) treatment protocols. METHODS: International multi-centre retrospective cohort study including 1483 NC-IVF, 1208 Min stim-IVF, and 1892 cIVF cycles performed in 8 IVF centres between 01.2022 and 03.2023. The five Min stim-IVF protocols analysed included low dose clomiphene citrate, aromatase inhibitors, low dose (≤ 100 IU) gonadotropins, each alone or in combination. For each IVF protocol, we assessed and modelled the transition probabilities of (i) each observed oocyte developing into a zygote, (ii) each observed zygote developing into a gestational sac and (iii) each observed zygote developing into a live birth. RESULTS: All modelled transition probabilities were found to be maximal in NC-IVF, minimal in cIVF with Min stim-IVF in between. The probability of transition from oocyte to zygote was 0.72 for NC-IVF, 0.56 to 0.65 for Min stim-IVF protocols and 0.54 for cIVF. The probability of transition from zygote to gestational sac was 0.21 for NC-IVF, 0.14 to 0.19 for Min stim-IVF and 0.09 for cIVF protocols and from zygote to live birth 0.16 for NC-IVF, 0.09 to 0.16 for Min stim-IVF and 0.06 for cIVF protocols. CONCLUSIONS: The transition probabilities of oocytes and zygotes appears to be higher in NC-IVF, followed by Min stim-IVF and then cIVF, suggesting that increasing dosages of gonadotropins might have a negative effect on oocyte/zygote development potential. TRIAL REGISTRATION: Clinicaltrial.gov: NCT05125497. Registration date 03.11.2021.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".