Visceral Adipose Tissue Depth in Early Pregnancy and Gestational Diabetes Mellitus - a Cohort Study
Bibliographic record
Abstract
Some studies have suggested that abdominal visceral adipose tissue depth (VAD) measured by ultrasound in early pregnancy, may predict the future onset of gestational diabetes mellitus (GDM). Wheter this is true, independent of pre-pregnancy body mass index (BMI), has been debated, leading the current study. A prospective cohort study was completed, in which VAD was measured at around 14 weeks' gestation. GDM was later assessed by an oral glucose tolerance test at 24 to 28 weeks, according to the IADPSG criteria. Logistic regression analysis and receiver operating curve (ROC) analysis were used to estimate the predictive value of VAD, above and beyond pre-pregnancy BMI. 627 pregnant women were enrolled, and 518 completed the study. VAD was measured at a mean of 14.4 weeks' gestation. 87 women (16.8%) subsequently developed GDM. The unadjusted odds ratio (OR) for developing GDM was 1.99 (95% CI 1.59-2.46) per 1-cm increase in VAD. After adjusting for maternal BMI and age, the OR was 2.00 (95% CI 1.61 to 2.50). The ROC under the curve for developing GDM was higher for VAD (0.70, 95% CI 0.63 to 0.75) than for pre-pregnancy BMI (0.57 95% CI 0.50 to 0.64) (p < 0.001). In conclusion, higher VAD may better predict GDM than pre-pregnancy BMI.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".