Does very advanced maternal age, with or without egg donation, really increase obstetric risk in a large tertiary center?
Bibliographic record
Abstract
OBJECTIVE: to assess complications of very advanced maternal age (VAMA) pregnancies ≥ 45 years with and without egg donation (ED). STUDY DESIGN: obstetric and neonatal complications were studied in 20,659 singleton pregnancies according to three maternal age groups: 20-39, 40-44 [advanced maternal age (AMA)] and ≥ 45 years (VAMA). Twenty pregnancies within the AMA/LAMA group that were achieved with ED were compared with age-matched controls. RESULTS: AMA mothers were more likely to have higher rates of preterm deliveries (OR 1.25), cesarean sections (OR 1.84) hypertension (OR 1.71) and diabetes (OR 2.45). Their newborns were more frequently small for gestational age (OR 1.30), and were more likely to have high rates of respiratory distress syndrome (OR 1.66), neonatal intensive care admission (OR 1.40) and perinatal/neonatal mortality (OR 1.83). VAMA pregnancies had >50% cesarean section rate and a high rate of diabetes (OR 2.29), hypertension (OR 1.54) and postpartum hemorrhage (OR 5.38). Congenital anomalies were more common among ED pregnancies. CONCLUSIONS: the higher rate of pregnancy complications for women ≥ 40 years is not further increased after 45 years of age.
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 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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".