Folate intake, markers of folate status and oral clefts: is the evidence converging?
Bibliographic record
Abstract
BACKGROUND: The ability of folic acid in the periconceptional period to prevent the occurrence of neural tube defects has stimulated tremendous interest in its effects on other health outcomes. Its possible effect on oral clefts has generated considerable debate. The purpose of this systematic review and meta-analysis was to assemble evidence on the role of folate in the aetiology of cleft lip with or without cleft palate (CL/P) and cleft palate only (CPO). METHODS: Medline, PubMed, Embase, Science Citation Index and the HuGE Published Literature Database were searched to February 2007 for articles related to oral clefts and multivitamin use, dietary folate, folic acid fortification, biochemical markers of folate status and polymorphisms in 5,10-methylenetetrahydrofolate reductase (MTHFR) and other genes involved in folate metabolism. Random effects meta-analysis was conducted when appropriate. RESULTS: Maternal multivitamin use was inversely associated with CL/P [odds ratio (OR) 0.75, 95% CI 0.65-0.88, based on 5717 cases and 59 784 controls] but to a lesser extent CPO (OR 0.88, 95% CI 0.76-1.01, 2586 cases and 59 684 controls). The volume of evidence on dietary folate, fortification and biochemical and genetic measures of folate status is substantially less; in aggregate, the evidence suggests that no association exists but there is substantial heterogeneity between studies. CONCLUSIONS: The evidence is not converging and there is no strong evidence for an association between oral clefts and folic acid intake alone. Multivitamin use in early pregnancy, however, may protect against oral clefts, especially CL/P although this association may be confounded by other lifestyle factors associated with multivitamin use.
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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 | 0.043 | 0.120 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.012 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".