Do Early Elevations in Amniotic Fluid Glucose and Insulin Predict the Risk for Gestational Diabetes Mellitus (GDM)?
Bibliographic record
Abstract
Screening and diagnosis for Gestational Diabetes Mellitus (GDM) is based on a series of abnormal oral glucose tolerance tests between 24–28 weeks in pregnant mothers. However, literature suggests that fetal metabolism might be perturbed earlier. Measuring fetal metabolomics using amniotic fluid (AF) may provide a window into this early in‐utero environment. Our objectives were (1) to determine if women subsequently diagnosed with GDM had elevated amniotic fluid (AF) glucose, insulin or insulin‐like‐growth‐factor‐binding‐protein 1 (IGFBP1) at the time of routine amniocentesis (12–22 wks) and (2) to quantify those amniotic fluid concentrations associated with increased risk for GDM using probability mapping. No women with pre‐existing diabetes were included. AF glucose and insulin were higher and IGFBP1 lower in women later diagnosed with GDM (p<0.01). Multiple logistic regression showed that maternal BMI, AF glucose, insulin and IGFBP1 were associated with later GDM diagnosis (p<0.05). Probability maps demonstrated that if high AF glucose (>144mg/mL) accompanied low IGFBP1 (< 20 mg/mL), GDM risk approached 80%. Interestingly, a greater GDM risk existed if either insulin or glucose was low and the other concentration elevated. We conclude that AF environment is sensitive to early fetal metabolic perturbations associated with GDM. This exposure to early elevations in AF glucose may provide an explanation for the inability of current GDM interventions to decrease the higher prevalence of NIDDM and GDM in adult GDM offspring. (Supported by Canadian Institutes for Health Research ‐ CIHR)
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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 | 0.004 |
| 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 | 0.001 |
| 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".