Treatment of Gestational Diabetes Mellitus and Maternal Risk of Diabetes After Pregnancy
Bibliographic record
Abstract
OBJECTIVE: To compare postpartum glucose tolerance between women treated for gestational diabetes mellitus (GDM) and those not treated. RESEARCH DESIGN AND METHODS: Metabolic testing was performed at 3 and 12 months postpartum in 599 women comprising the following gestational glucose tolerance groups: 1) normal glucose challenge test (GCT) and oral glucose tolerance test (OGTT) during pregnancy, 2) abnormal GCT with normal OGTT, 3) gestational impaired glucose tolerance, 4) mild untreated GDM, and 5) severe treated GDM. RESULTS: Birth weight progressively increased across groups 1-4 before falling steeply in treated GDM (P < 0.0001). In contrast, at 3 and 12 months, insulin sensitivity and β-cell function progressively decreased across the five groups, mirrored by rising fasting and 2-h glucose (all P < 0.0001). Accordingly, prevalence of prediabetes/diabetes at 12 months increased in a stepwise manner across groups 1-5 (2.8%, 9.6%, 13.5%, 21.5%, and 32.6%, respectively; P < 0.0001). CONCLUSIONS: Treating GDM lowers birth weight but does not disrupt the association between gestational glycemia and maternal prediabetes/diabetes after pregnancy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.001 | 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".