MATERNAL AGE AND NEURODEVELOPMENTAL OUTCOMES OF PRETERM INFANTS <29 WEEKS GESTATIONAL AGE
Bibliographic record
Abstract
BACKGROUND: Maternal age at pregnancy has shown right shift, increasing in recent decades. Advanced maternal age is associated with increased obstetrical and perinatal complications. The impact of maternal age on neurodevelopmental (ND) outcomes of preterm infants remains unknown. OBJECTIVES: To assess the impact of maternal age on ND outcomes of infants born <29 weeks GA at 18-24 months. DESIGN/METHODS: Retrospective cohort study of infants born <29 weeks GA between April 2009 and September 2011 and admitted to Canadian NICUs. The primary outcome was a composite of death or ND impairment (NDI)/severe NDI (SNDI) at 18-24 months assessed using the Bayley-III. Maternal age was categorized into 4 age groups: 15-19, 20-34 (reference age group), 35-39, and ≥40 years. Baseline characteristics and short-term neonatal outcomes were compared using appropriate statistics. Association between maternal age and outcomes was assessed using logistic regression after adjusting for confounders. RESULTS: Of 3691 eligible infants, 2652 had complete data and were included in the analysis. Significant differences in maternal characteristics existed among the 4 maternal age groups; no differences in neonatal characteristics existed other than incidence of BPD (Table 1). The primary outcome of death or SNDI was significantly reduced for infants of mothers≥40 years after controlling for confounders (Table 1). CONCLUSION: Maternal age≥40 years is associated with lower rates of death or SNDI at 18-24 months among infants born <29 weeks GA. These findings may help to inform future antenatal counseling. Maternal, neonatal and outcome characteristics
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".