Vitamin D during pregnancy and the neurodevelopment of the child: Systematic review
Bibliographic record
Abstract
© Copyright 2019: Editum. ISSN print edition: 0212-9. Background: A deficiency of vitamin D during pregnancy has a negative impact on maternal-infant health. Objective: To evaluate the effect of vitamin D status during pregnancy on offspring neurodevelopmental outcomes. Selection of studies: We explored studies that linked maternal vitamin D status with offspring neurodevelopmental outcomes. The studies selected were identified by systematically reviewing the scientific literature published in PubMed/MEDLINE, Scopus and Cochrane until January 2018. The quality of the studies was evaluated using the Newcastle-Ottawa scale. Results: 164 studies were identified and reviewed for selection. This systematic review, which comprises eleven studies (ten of a high methodological quality and one moderate), shows that mothers with vitamin D levels <50 nmol/L during pregnancy had offspring with poorer mental, motor and language development compared to mothers with concentrations ≥50 nmol/L. Conclusion: There is still not enough scientific evidence to confirm the relationship between prenatal vitamin D deficiency and offspring neurodevelopmental outcomes. However, recent data suggest a detrimental effect on the mental, motor and language development of offspring.
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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 | 0.005 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".