Gestational Diabetes Mellitus and Folic Acid Supplementation in Pregnant Women: A Systematic Review
Bibliographic record
Abstract
Background: Gestational diabetes mellitus (GDM) is a common pregnancy disorder screened for between the 24th and 28th weeks of gestation using oral glucose tolerance test. GDM has maternal and fetal health implications. Objective: To assess the relation between folic acid supplementation in pregnant women and the risk of developing GDM. Search Strategy: The search employed topic-based strategies designed for each database in June 2020. Databases searched were Pubmed, Cochrane Library, Embase and Lebanese American University online database. Selection Criteria: Studies eligible were those targeting the association of GDM development and folic acid supplementation, including pregnant women who have developed GDM and pregnant women who were on folic acid supplementation and developed GDM. Both interventional and observational studies were included. Data Collection and Analysis: Two reviewers extracted the data independently. A third reviewer checked the data for consistency and clarity. Data extracted included the sample characteristics, sample size and outcomes. Cohen’s κ was used to assess agreement between reviewers. All tools and processes were piloted prior to use. Risk of bias was assessed using the Newcastle-Ottawa Scale. Data was presented in a tabulated form. Main Results: Six studies showed a proportional relation between folic acid intake and GDM, two reported a protective effect, and one cohort found no association. Conclusion: The inconsistent results made the formulation of a definitive conclusion difficult. Hence, larger studies are needed.
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".