The effects of age, mature oocyte number, and cycle number on cumulative live birth rates after planned oocyte cryopreservation
Bibliographic record
Abstract
PURPOSE: To examine the effects of age, mature oocyte number, and cycle number on cumulative live birth rates after planned oocyte cryopreservation (OC), with the goal of developing a patient counselling tool. METHODS: We performed a retrospective cohort study of all patients with ≥ 1 autologous oocyte thaw at our university-affiliated fertility center before 12/31/2023. Patients were included if they (1) had a live birth or ongoing pregnancy > 12 weeks from OC, or (2) used all oocytes and euploid/untested embryos from OC. Primary outcome was cumulative live birth / ongoing pregnancy rate (CLBR). RESULTS: 527 patients with 1 OC cycle, 149 patients with 2 OC cycles, and 55 patients with ≥ 3 OC cycles were included. Overall CLBR was 43%. CLBR was > 70% among patients who thawed ≥ 20 mature oocytes that were cryopreserved at age < 38 years. Multiple logistic regression showed that age at first OC and total number of mature oocytes thawed independently predicted CLBR, but number of OC cycles did not. CONCLUSION: Patients must be counselled that younger age at OC and more mature oocytes improve CLBR. However, additional OC cycles do not independently improve CLBR. Our results can help patients decide whether to pursue additional OC cycles to obtain more 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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".