Difference in Visceral Adipose Tissue in Pregnancy and Postpartum and Related Changes in Maternal Insulin Resistance
Bibliographic record
Abstract
OBJECTIVE: To measure the difference between first-trimester and postpartum visceral adipose tissue (VAT), the agreement of this difference with change in body mass index, and whether a difference in VAT is associated with insulin resistance or glucose mishandling. METHODS: Prospective study of 93 women with singleton pregnancies without a history of diabetes. Visceral adipose tissue depth was sonographically assessed at 11 to 14 weeks and at 6 to 12 weeks postpartum. Metabolic measures, sampled at 24 to 28 weeks and 6 to 12 weeks postpartum, included homeostatic model assessment of insulin resistance, insulin sensitivity index composite, and area under the 75-g oral glucose tolerance test curve. RESULTS: First-trimester VAT depth explained only 37% (95% confidence interval [CI], 22-52) of the variation in postpartum VAT depth. There was limited agreement between the net change in postpartum minus first-trimester VAT depth and that same net change for body mass index (Cohen's kappa, 0.26; 95% CI, 0.05-0.47). Those with a net gain in VAT depth demonstrated poorer insulin sensitivity index postpartum than women with a net regression in VAT depth-a difference of -2.0 (95% CI, -3.3 to -0.69). CONCLUSION: Sonographic assessment of postpartum VAT is feasible and may provide insight to metabolic changes between pregnancy and postpartum, beyond body mass index.
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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 | 0.006 |
| 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".