Prevalence of metabolic markers of insulin resistance in offspring of gestational diabetes pregnancies
Bibliographic record
Abstract
In utero hyperglycemia has been associated with insulin resistance (IR) in children; however, there are limited data in low-risk populations. The purpose of this study was to describe the prevalence of metabolic markers of IR in a primarily Caucasian cohort of gestational diabetes mellitus (GDM) offspring aged 7-11 yr (mean 9.1) and to correlate offspring with maternal indexes. Sixty-eight children were recruited through a follow-up study of women who participated in a randomized controlled trial of minimal intervention vs. tight glycemic control for GDM. All participants had a fasting plasma glucose (FPG), insulin, total cholesterol, high-density lipoprotein cholesterol (HDL-chol), triglyceride (TG) level, and a 2-h oral glucose tolerance test. We calculated homeostasis model assessment (HOMA) and recorded body mass index and waist circumference (WC). Criteria for metabolic syndrome for children included: FPG > 6.0 mmol/L, HDL-chol < 1.03 mmol/L, TG > 1.24 mmol/L, WC > 90% for age and gender, and 2-h glucose > 7.8 mmol/L. Among these children, 45 (66%), 17 (25%), 5 (7%), and 1 (1.5%) had zero, one, two, or three metabolic markers of IR, respectively. Hypertriglyceridemia (21%) was most prevalent, with no child having an elevated FPG. WC (p = 0.018) and TG (p = 0.005) were strong predictors of IR in the offspring after adjustment for age, gender, birthweight, family history, and maternal IR. Maternal and offspring HDL-chol, TG, WC, and HOMA but not fasting or 2-h glucose levels were significantly correlated. We conclude that metabolic markers of IR in children exposed to GDM may be present in the absence of abnormal fasting or 2-h glucose values. Screening strategies that focus on glucose levels may need to be reconsidered to institute early intervention with lifestyle changes for children at risk.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".