The association of maternal fat-soluble antioxidants in early pregnancy with gestational diabetes mellitus: a prospective cohort study
Bibliographic record
Abstract
Abstract Introduction Oxidative stress is linked to the development of gestational diabetes mellitus (GDM). Maternal antioxidant vitamins in early pregnancy may play a role in GDM occurrence. We aimed to investigate the associations of vitamins A and E in early pregnancy with the risk of GDM and to explore whether these antioxidant vitamins can be biomarkers for the early prediction of GDM. Methods We carried out a prospective cohort study conducted in Beijing and enrolled pregnant women ( n = 667) with vitamins A and E measurements at 9 weeks (IQR 8–10) of gestation and having one-step GDM screened with a 75-g oral glucose tolerance test between 24 and 28 weeks of gestation. Results The vitamin A levels in early pregnancy were significantly higher in women with GDM than in those without GDM ( p < 0.0001) and positively correlated with fasting blood glucose. In multivariate models, vitamin A levels were significantly associated with GDM (OR, 1.46; 95% CI: 1.14–1.88; p = 0.0032) per SD. A significant trend of risk effect on GDM risk across quartiles of vitamin A was observed ( p trend = 0.016). No significant association of serum vitamin E with GDM was observed overall. However, a noted trend of protective effect on GDM risk across quartiles of vitamin E/cholesterol ratio was observed ( p trend = 0.043). In ROC analysis, the multivariate model consisting of vitamin A and other risk factors showed the best predictive performance (AUC: 0.760; 95% CI: 0.705–0.815; p < 0.001). Conclusions Higher levels of vitamin A in early pregnancy were significantly associated with an increased risk of GDM. Vitamin A has the potential to be a biomarker indicating pathogenesis of GDM.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".