Liver Markers and Development of the Metabolic Syndrome
Bibliographic record
Abstract
Nonalcoholic fatty liver disease (NAFLD) is emerging as a component of the metabolic syndrome, although it is not known whether markers of NAFLD, including elevated concentrations of aspartate aminotransferase (AST), alanine aminotransferase (ALT), and alkaline phosphatase (ALK), predict the development of metabolic syndrome. Our objective was to investigate the associations of elevated AST, ALT, and other liver markers, including C-reactive protein (CRP), with incident National Cholesterol Education Program-defined metabolic syndrome among 633 subjects in the Insulin Resistance Atherosclerosis Study who were free of metabolic syndrome at baseline. Insulin sensitivity (Si) and acute insulin response (AIR) were directly measured from the frequently sampled intravenous glucose tolerance test among African-American, Hispanic, and non-Hispanic white subjects aged 40-69 years. After 5.2 years, 127 individuals had developed metabolic syndrome. In separate logistic regression models adjusting for age, sex, ethnicity, clinic, and alcohol consumption, subjects in the upper quartiles of ALT, ALK, and CRP were at significantly increased risk of incident metabolic syndrome compared with those in the lowest quartile: ALT, odds ratio 2.50 (95% CI 1.38-4.51); ALK, 2.28 (1.24-4.20); and CRP, 1.33 (1.09-1.63). Subjects in the upper quartile of the AST-to-ALT ratio were at significantly reduced metabolic syndrome risk (0.40 [0.22-0.74]). After further adjustment for waist circumference, Si, AIR, and impaired glucose tolerance, the associations of ALT and the AST-to-ALT ratio with incident metabolic syndrome remained significant (ALT, 2.12 [1.10-4.09]; the AST-to-ALT ratio, 0.48 [0.25-0.95]). These associations were not modified by ethnicity or sex, and they remained significant after exclusion of former and heavy drinkers. In conclusion, NAFLD markers ALT and the AST-to-ALT ratio predict metabolic syndrome independently of potential confounding variables, including directly measured Si and AIR.
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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".