Each Degree of Glucose Intolerance in Pregnancy Predicts Distinct Trajectories of β-Cell Function, Insulin Sensitivity, and Glycemia in the First 3 Years Postpartum
Bibliographic record
Abstract
OBJECTIVE: Glucose intolerance in pregnancy predicts an increased risk of future type 2 diabetes mellitus (T2DM) that is proportional to the severity of antepartum dysglycemia (i.e., highest in women with gestational diabetes mellitus [GDM], followed by those with milder dysglycemia). However, the pathophysiologic changes driving this risk are not known. Thus, we evaluated the longitudinal changes in β-cell function, insulin sensitivity, and glycemia in the first 3 years postpartum after gestational dysglycemia. RESEARCH DESIGN AND METHODS: A total of 337 women underwent glucose challenge test (GCT) and oral glucose tolerance test (OGTT) in pregnancy, followed by repeat OGTT at 3 months, 1 year, and 3 years postpartum. The antepartum GCT/OGTT identified four gestational glucose tolerance groups: GDM (n = 105); gestational impaired glucose tolerance (GIGT; n = 60); abnormal GCT, followed by normal glucose tolerance (NGT) on the OGTT (abnormal GCT NGT; n = 96); and normal GCT with NGT (n = 76). RESULTS: At each of 3 months, 1 year, and 3 years postpartum, the prevalence of glucose intolerance increased from normal GCT NGT to abnormal GCT NGT to GIGT to GDM (all P < 0.001), whereas β-cell function, assessed by the Insulin Secretion-Sensitivity Index-2 (ISSI-2), and insulin sensitivity (Matsuda index), progressively decreased across the groups (all P < 0.002). Each group predicted distinct trajectories of ISSI-2, Matsuda index, and fasting and 2-h glucose (all P < 0.001). Notably, GDM, GIGT, and abnormal GCT NGT predicted varying rates of declining β-cell function and insulin sensitivity, as well as rising glycemia, compared with normal GCT NGT. CONCLUSIONS: Each degree of gestational glucose intolerance predicts distinct trajectories of β-cell function, insulin sensitivity, and glycemia in the first 3 years postpartum that drive their differential risk of future T2DM.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".