Is Older Maternal Age a Risk Factor for Preterm Birth and Fetal Growth Restriction? A SystematicReview
Bibliographic record
Abstract
To determine if there was an association between advancing maternal age and adverse pregnancy outcomes (preterm delivery and small-for-gestational-age births), a systematic review was conducted based on a comprehensive search of the literature from 1985 to 2002. Ten studies met the following inclusion criteria: (1) assessed risk factors for preterm birth by subtype (i.e., idiopathic preterm labor, preterm premature rupture of membranes) and small-for-gestational-age (SGA) birth (fetal growth restriction); (2) used acceptable definitions of these outcomes; (3) were published between January 1985 and December 2002; (4) were restricted to studies that have considered preterm birth due to idiopathic preterm labor or premature rupture of membranes or both; (5) were restricted to singleton live births; (6) were conducted in a developed country; and (7) were published in English. The majority of the studies reviewed found that older maternal age was associated with preterm birth. There is insufficient evidence to determine if older maternal age is an independent and direct risk factor for preterm birth and SGA birth, or a risk marker that exerts its influence on gestational age or birth weight or both through its association with age-dependent confounders. Future research is needed to quantify the independent and unconfounded impact of delayed childbearing on neonatal outcomes, as well as to identify the pathways involved.
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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 | 0.004 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".