Risk of early progression to prediabetes or diabetes in women with recent gestational dysglycaemia but normal glucose tolerance at 3‐month postpartum
Bibliographic record
Abstract
OBJECTIVE: Both gestational diabetes mellitus (GDM) and milder glucose intolerance in pregnancy identify women who are at risk of developing type 2 diabetes. While some of these women will have prediabetes or diabetes in the early postpartum, most will have normal glucose tolerance (NGT), despite their future diabetic risk. In this context, we sought to evaluate the risk of early progression to dysglycaemia in women with NGT at 3-month postpartum and identify predictors thereof. METHODS: Three hundred and twenty-five women with varying degrees of gestational dysglycaemia but NGT on oral glucose tolerance test (OGTT) at 3-month postpartum underwent repeat OGTT at 12-month postpartum. RESULTS: By 12-month postpartum, 10% of the study population and 17.1% of those with recent GDM had progressed to dysglycaemia (primarily impaired glucose tolerance). At 3-month postpartum, compared to nonprogressors, the progressors had (i) higher BMI (P = 0.0023), LDL (P = 0.0017), triglycerides (P = 0.0002), leptin (P = 0.0021) and C-reactive protein (P = 0.043), and (ii) lower HDL (P = 0.0026) and adiponectin (P = 0.045). Notably, although all women had NGT at the time, each of the following glucose-related parameters from the OGTT at 3-month postpartum emerged as a significant independent predictor of progression on logistic regression analyses: area-under-the-glucose-curve (OR = 1.37, 95% CI: 1.13-1.65; P = 0.0012); sum of the glucose values (OR = 1.16, 95% CI: 1.05-1.29; P = 0.0042); and having a delayed blood glucose peak (occurring >30 min postload) (OR = 2.89, 95% CI: 1.29-6.45; P = 0.0097). CONCLUSIONS: A normal OGTT at 3-month postpartum does not necessarily provide assurance of a low risk of progression to prediabetes. Glucose-related measures during this OGTT may identify those women at highest risk for early progression.
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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 | 0.000 | 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 | 0.001 |
| 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".