Bibliographic record
Abstract
OBJECTIVE: To examine associations of neonatal adiposity with maternal glucose levels and cord serum C-peptide in a multicenter multinational study, the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study, thereby assessing the Pederson hypothesis linking maternal glycemia and fetal hyperinsulinemia to neonatal adiposity. RESEARCH DESIGN AND METHODS: Eligible pregnant women underwent a standard 75-g oral glucose tolerance test between 24 and 32 weeks gestation (as close to 28 weeks as possible). Neonatal anthropometrics and cord serum C-peptide were measured. Associations of maternal glucose and cord serum C-peptide with neonatal adiposity (sum of skin folds >90th percentile or percent body fat >90th percentile) were assessed using multiple logistic regression analyses, with adjustment for potential confounders, including maternal age, parity, BMI, mean arterial pressure, height, gestational age at delivery, and the baby's sex. RESULTS: Among 23,316 HAPO Study participants with glucose levels blinded to caregivers, cord serum C-peptide results were available for 19,885 babies and skin fold measurements for 19,389. For measures of neonatal adiposity, there were strong statistically significant gradients across increasing levels of maternal glucose and cord serum C-peptide, which persisted after adjustment for potential confounders. In fully adjusted continuous variable models, odds ratios ranged from 1.35 to 1.44 for the two measures of adiposity for fasting, 1-h, and 2-h plasma glucose higher by 1 SD. CONCLUSIONS: These findings confirm the link between maternal glucose and neonatal adiposity and suggest that the relationship is mediated by fetal insulin production and that the Pedersen hypothesis describes a basic biological relationship influencing fetal growth.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".