Short interpregnancy intervals, maternal folate levels, and infants born small for gestational age: a preliminary study in a Canadian supplement-using population
Bibliographic record
Abstract
Short interpregnancy intervals (SIPI) have been associated with increased risks for adverse neonatal outcomes including preterm delivery and infants small for gestational age (SGA). It has been suggested that mechanistically, adverse neonatal outcomes after SIPI arise due to insufficient recovery of depleted maternal folate levels prior to the second pregnancy. However, empirical data are lacking regarding physiological folate levels in pregnant women with SIPI and relationships between quantified physiological folate levels and outcomes like SGA. Therefore, we sought to test 2 hypotheses, specifically that compared with controls women with SIPI would: (i) have lower red blood cell folate (RBCF) levels and (ii) be more likely to have SGA infants (defined as <10th percentile). Using data collected in British Columbia, Canada, for a larger study on perinatal psychopathology, we documented supplementation use and compared prenatal RBCF levels and proportion of SGA infants between women with SIPI (second child conceived ≤24 months after previous birth, n = 26) and matched controls (no previous pregnancies, or >24 months between pregnancies, n = 52). There were no significant differences in either mean RBCF levels (Welch's t test, p = 0.7) or proportion of SGA infants (Fisher's exact test, p = 0.7) between women with SIPI and matched controls. We report the first data about RBCF levels in the context of SIPI. If confirmed, our finding of no relationship between these variables in this population suggests that continued folic acid supplementation following an initial pregnancy mitigates folate depletion. We found no relationship between SIPI and SGA.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".