The Impact of a Gluten-Free Diet on Pregnant Women with Celiac Disease: Do We Need a Guideline to Manage Their Health?
Bibliographic record
Abstract
A healthy and balanced diet is a critical requirement for pregnant women as it directly influences both the mother’s and infant’s health. Poor maternal nutrition can lead to pregnancy-related complications with undesirable effects on the fetus. This requirement is equally important for pregnant women with celiac disease (CD) who are already on a gluten-free diet (GFD). Although the GFD is the sole treatment option for CD, it still presents some challenges and confusion for celiac women who wish to conceive. Poorly managed CD has been linked to miscarriages, preterm labor, low birth weight, and stillbirths. Current CD guidelines primarily focus on screening, diagnosis, treatment, and management but lack an evidence-based approach to determine appropriate energy requirements, recommended weight gain during pregnancy, target macronutrient distribution from the diet, the recommended intake of vitamins and minerals from diet and/or supplementation, timing for starting supplementation, and advised portions of gluten-free foods during pregnancy. We recommend and call for the development of such guidelines and/or authoritative papers in the future.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".