Relationship Between Metabolic Syndrome, Alanine Aminotransferase Levels, and Liver Disease Severity in a Multiethnic North American Cohort With Chronic Hepatitis B
Bibliographic record
Abstract
OBJECTIVE Metabolic syndrome (MS) is prevalent and is associated with adverse outcomes of liver disease. We evaluated the prevalence of MS and its influence on alanine aminotransferase (ALT) levels and fibrosis, as estimated by the aspartate aminotransferase–to–platelet ratio index (APRI), in a large, multiethnic North American cohort with chronic hepatitis B (HBV) infection. RESEARCH DESIGN AND METHODS Adults with chronic HBV from 21 centers within the U.S. and Canada were evaluated at baseline and for up to 5 years (median 3.7 years) of follow-up. MS was defined as the presence of at least three of five criteria including waist circumference, blood pressure, glucose, triglyceride, and HDL levels. RESULTS Analysis included 777 participants, of whom 171 (22%) had MS. Participants with MS (vs. those without MS) were older (median age 54.4 vs. 40.2 years), more often male (61% vs. 51%), and born in the U.S./Canada or had immigrated >20 years ago (60% vs. 43%). MS was not associated with ALT or APRI at baseline. Upon adjusted multivariable analysis of serial ALT values, ALT was significantly higher (mean 12%; P = 0.02) among those with MS at baseline and even higher (mean 19%; P = 0.003) among those with persistent MS compared with those with persistent absence of MS. MS was not associated with serial APRI on follow-up. CONCLUSIONS MS was prevalent in this HBV cohort and was independently associated with higher ALT levels longitudinally. These findings highlight the importance of screening for MS and the potential for MS to influence ALT and its interpretation in the context of HBV treatment decisions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".