Abnormal screening glucose challenge test in pregnancy and future risk of diabetes in young women
Bibliographic record
Abstract
AIMS: Pregnant women commonly undergo screening for gestational diabetes mellitus (GDM) using a 50-g glucose challenge test (GCT), followed by a diagnostic oral glucose tolerance test (OGTT) in those women in whom the GCT is abnormal. Although it has long been recognized that GDM is associated with subsequent Type 2 diabetes, it has recently emerged that any degree of abnormal antepartum glucose homeostasis predicts an increased risk of postpartum glucose intolerance. Thus, in this context, we sought to determine whether women who have a pregnancy complicated by an abnormal GCT, but who do not have GDM, are at increased risk of subsequent diabetes, compared with their peers with an abnormal GCT. METHODS: A population-based, retrospective cohort study was conducted. Women referred for an antepartum OGTT indicative of an abnormal GCT (n = 15 381), but without GDM, were matched (for age, region, socioeconomic status, and year of delivery) with up to four other women without such referral (n = 61 237). The two cohorts were followed over a median 6.4 years for the development of diabetes. RESULTS: The rate of incident diabetes was 5.04 cases per 1000 person-years in the cohort of women who underwent an antepartum OGTT, compared with 1.74 cases per 1000 person-years in women without an OGTT. The hazard ratio for subsequent diabetes in women with an antepartum OGTT was 2.56 (95% confidence interval 2.28, 2.87) (P < 0.0001). CONCLUSIONS: Even in the absence of GDM, abnormal screening GCT in pregnancy is associated with an increased future risk of diabetes in young women.
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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 | 0.001 | 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".