Non-Alcoholic Fatty Liver Disease in Early Pregnancy Predicts Dysglycemia in Mid-Pregnancy: Prospective Study
Bibliographic record
Abstract
OBJECTIVES: Non-alcoholic fatty liver disease (NAFLD) is mediated by insulin resistance, as is gestational diabetes mellitus (GDM). NAFLD has not been studied in relation to GDM. The objective of this study was to assess the association between first-trimester sonographic findings of NAFLD, and both dysglycemia and GDM in mid-pregnancy. METHODS: We followed a prospective cohort design at a large obstetrics clinic in Toronto, Ontario with 476 women enrolled in early pregnancy. NAFLD was assessed by ultrasound at 11-14 weeks gestation, and standardized images were independently scored by two ultrasonographers for the presence of hepatorenal contrast (one finding) and/or blurring of the intrahepatic vessels (one finding), relative to neither being present. Logistic regression analysis was used to generate odds ratios (ORs) and 95% confidence interval (CI) for the relation between 0, 1, or 2 sonographic findings of NAFLD and the composite outcome of impaired fasting glucose, impaired glucose tolerance, or GDM at 24-28 weeks gestation, determined by a fasting 75-g oral glucose tolerance test. ORs were adjusted (aOR) for maternal age, ethnicity, first-degree relative with type 2 DM, body mass index (BMI) at 11-14 weeks gestation, and change in BMI from 11-14 to 24-28 weeks gestation. RESULTS: Fifty out of 476 women (10.5%) developed the composite outcome. The presence of 1 (aOR 2.0, 95% CI: 1.0-4.1) or 2 (aOR 2.9, 95% CI: 1.0-18.4) sonographic features of NAFLD predicted the composite outcome. Limiting the analysis to ≥1 feature vs. none, the aOR was 2.2 (95% CI: 1.1-4.3). CONCLUSIONS: Sonographic assessment of NAFLD is a semiquantitative measure, with limited ability to detect small amounts of hepatic steatosis, or to distinguish various stages of NAFLD. First-trimester sonographic evidence of NAFLD predicts dysglycemia in mid-pregnancy.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".