Advanced maternal age: ethical and medical considerations for assisted reproductive technology
Bibliographic record
Abstract
OBJECTIVES: This review explores the ethical and medical challenges faced by women of advanced maternal age who decide to have children. Assisted reproductive technologies (ARTs) make post-menopausal pregnancy physiologically plausible, however, one must consider the associated physical, psychological, and sociological factors involved. METHODS: A quasi-systematic review was conducted in PubMed and Ovid using the key terms post-menopause, pregnancy + MeSH terms [donations, hormone replacement therapy, assisted reproductive technologies, embryo donation, donor artificial insemination, cryopreservation]. Overall, 28 papers encompassing two major themes (ethical and medical) were included in the review. CONCLUSION: There are significant ethical considerations and medical (maternal and fetal) complications related to pregnancy in peri- and post-menopausal women. When examining the ethical and sociological perspective, the literature portrays an overall positive attitude toward pregnancy in advanced maternal age. With respect to the medical complications, the general consensus in the evaluated studies suggests that there is greater risk of complication for spontaneous pregnancy when the mother is older (eg, >35 years old). This risk can be mitigated by careful medical screening of the mother and the use of ARTs in healthy women. In these instances, a woman of advanced maternal age who is otherwise healthy can carry a pregnancy with a similar risk profile to that of her younger counterparts when using donated 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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".