Gestational diabetes mellitus and linear growth in early childhood
Bibliographic record
Abstract
Introduction: Gestational diabetes mellitus (GDM) is a common pregnancy complication with potential short- and long-term adverse consequences for both mothers and fetuses. It is unclear whether GDM affects linear growth in the offspring; research data are limited and inconsistent. Methods: In a prospective birth cohort in Shanghai (n=2055 children; 369 born to mothers with GDM). We sought to evaluate the impact of GDM on longitudinal linear growth in early childhood. Length/height was measured in children at birth, 6 weeks, 6 months, 1, 2 and 4 years of age. Multivariate linear regression and generalized estimating equation models were employed to assess the impact of GDM on length/height for age Z score (LAZ/HAZ). Results: . euglycemic mothers. Adjusting for maternal and child characteristics, the children of mothers with GDM had consistently lower LAZ/HAZ compared to children of mothers without diabetes at ages 6 weeks, 6 months, 1, 2 and 4 years. GDM was associated with a 0.12 (95% confidence intervals 0.04-0.21) deficit in LAZ/HAZ in the growth trajectory from birth to age 4 years after adjusting for maternal and child characteristics. Discussion: GDM was associated with impaired longitudinal linear growth in early childhood. Further studies are warranted to understand the long-term impact on stature and health.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".