Bibliographic record
Abstract
PURPOSE OF REVIEW: This article presents an overview of the most recent scientific evidence of the role of maternal vitamin D on pregnancy outcomes, with a particular emphasis on those articles in the English-language literature published between 1 January 2013 and 1 July 2014 in PubMed. RECENT FINDINGS: Low levels of vitamin D status, as measured by 25-hydroxyvitamin D [25(OH)D], are common in pregnant women. Meta-analysis of observational studies has demonstrated positive associations between vitamin D status and adverse pregnancy outcomes such as preeclampsia, gestational diabetes mellitus, preterm birth and small-for-gestational age. There was heterogeneity among studies in terms of design, population, geographic location, definitions of exposure and outcome, gestational age at sampling, confounding factors and approach to analyses. Randomized controlled trials (RCTs) indicate that vitamin D supplementation during pregnancy optimizes maternal and neonatal vitamin D status. SUMMARY: Recent evidence supports that low maternal vitamin D status is associated with an increased risk of adverse pregnancy outcomes. Interventional studies demonstrate that vitamin D supplementation during pregnancy optimizes maternal and neonatal vitamin D status. Large, well designed, multicentre RCTs are required to determine whether vitamin D supplementation in pregnant women with low vitamin D status reduces the risk of adverse pregnancy outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".