Advanced maternal age and adverse obstetrical and neonatal outcomes of singleton pregnancies
Bibliographic record
Abstract
Abstract Objective To assess the impact of advanced maternal age on pregnancy and childbirth outcomes of singleton pregnancies. Study design We retrospectively assessed singleton pregnant mothers who gave birth at Khaleej-e-Fars Hospital in Bandar Abbas, Iran, from January 2020 to January 2022. Demographic and obstetrical factors include educational level, medical insurance, residency place, access to prenatal care facilities, number of prenatal care visits, smoking status, gestational age, parity, infertility, maternal comorbidities, preeclampsia, eclampsia, preterm birth, low birth weight (LBW), intrauterine growth restriction (IUGR), macrosomia, placenta abnormalities (previa/acreta), placenta abruption, chorioamnionitis, meconium fluid, fetal distress, methods of delivery, rate of cesarean section (CS), perineal lacerations, postpartum hemorrhage, childbirth injury, shoulder dystocia, congenital malformation, neonatal asphyxia, and unfavorable maternal and neonatal outcome were compared between two groups. The Chi-square test assessed the relationship between categorical factors and maternal age groups. The influence of advanced maternal age on the risk of unfavorable pregnancy outcomes was evaluated using bivariate and multivariate logistic regression. Results Of 8354 singleton deliveries, 22.2% belonged to advanced-age mothers. Advanced-age mothers had less education than those aged 20–34 years old. Chronic hypertension, cardiovascular disease, overt diabetes, and thyroid dysfunction were more prevalent among advanced-age mothers. Compared with mothers aged 20–34 years, mothers aged 35 years and higher had a significantly higher risk of gestational diabetes (aOR: 3.18, 95%CI: 1.56–6.95), preeclampsia (aOR: 2.91, 95%CI: 1.35–4.72), placenta abnormalities (aOR: 1.09, 95%CI: 0.77–1.94), CS (aOR: 3.16, 95%CI: 1.51–3.87), postpartum hemorrhage (aOR: 1.94, 95%CI: 1.24–2.61), intensive care unit admission (aOR: 1.36, 95% CI: 1.15–1.99), LBW (aOR: 1.35, 95%CI: 0.97–2.96), preterm birth (aOR: 2.36, 95%CI: 1.65–4.83), stillbirth (aOR: 1.18, 95%CI: 1.01–3.16), and neonatal intensive care admission (aOR: 2.09, 95%CI: 0.73–3.92). According to bivariate regression, the risk of meconium fluid was lower in advanced-age mothers; however, the result of multivariate logistic regression found no correlation between advanced age and the Incidence of meconium fluid. Conclusion Advanced-age mothers are at increased risk of adverse pregnancy and childbirth outcomes, which persist even after adjusting for several potential confounders.
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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 | 0.001 | 0.020 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".