Paternal age predicts live birth in women above 40 years of age undergoing in-vitro fertilization (IVF)
Bibliographic record
Abstract
Purpose: To determine which factors predict pregnancy outcome in women aged 40 years and above who underwent in-vitro fertilization. Method: We conducted a retrospective case-control study of 631 women aged 40–46 years, who underwent a total of 904 IVF cycles with autologous gametes. We used stepwise logistic regression analysis to develop predictors of pregnancy, clinical pregnancy and live birth outcomes. Data are presented as mean ± SD, percentage and confidence intervals. Results: Predictors of live birth included maternal (95% CI: 0.36–0.78) and paternal (95% CI: 0.62–0.94) age, the number of follicels > 14 mm (95% CI: 1.2–3.2), the number of oocytes collected (95% CI: 1.3–2.9) the number of metaphase II oocytes (95% CI: 1.3–2.4) and the number of cleavage stage embryos (95% CI: 1.8–2.6). The predictors of pregnancy and clinical pregnancy were similar but did not include male age (P > 0.05). To further determine the role of male age in live birth a control group of women younger than 40 years was collected. Male age was not a significant predictor of live birth among younger women (P = 0.42). Conclusions: Female age and better ovarian stimulation were confirmed as predictors of outcomes in older women doing IVF. However, male age was also noted to be a significant individual predictor of live birth in women over 40 years of age, but not in younger women doing IVF.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".