Hepatitis C Virus-Infected Patients Are ‘Spared’ from the Metabolic Syndrome but Not from Insulin Resistance. A Comparative Study of Nonalcoholic Fatty Liver Disease and Hepatitis C Virus-Related Steatosis
Bibliographic record
Abstract
BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) and chronic hepatitis C feature steatosis and insulin resistance (IR), conditions associated with the metabolic syndrome (MS). OBJECTIVES: To assess the prevalence of MS and determinants of IR in patients with NAFLD and chronic hepatitis C. METHODS: Ninety-three consecutive patients with NAFLD, 97 with chronic hepatitis C virus (HCV) genotypes 1 and 2, and 182 'healthy' controls without steatosis were enrolled in the present study. The prevalence of MS was assessed by modified Adult Treatment Panel III criteria and IR by the homeostasis model assessment of insulin resistance (HOMA-IR). IR was defined as the 75th percentile of the HOMA-IR of control subjects. RESULTS: While the prevalence of IR was similar in NAFLD and HCV-infected subjects (70.0% and 78.7%, respectively), the prevalence of MS was significantly higher in NAFLD patients than in HCV-infected patients (27.9% versus 4.1%) and in controls (5.6%). With multivariate analysis, IR was predicted by body mass index (OR 1.263; 95% CI 1.078 to 1.480) and triglyceridemia (OR 1.011; 95% CI 1.002 to 1.020) in NAFLD and by sex (OR for female sex 0.297; 95% CI 0.094 to 0.940) and fibrosis stage (OR 2.751; 95% CI 1.417 to 5.340) in chronic hepatitis C. CONCLUSIONS: IR is independently associated with body mass index and triglyceridemia in NAFLD, sex and fibrosis in chronic HCV infection, and has a higher prevalence in NAFLD and chronic hepatitis C than in controls. However, the frequency of MS in HCVinfected patients, similar to that of controls, is significantly lower than that seen in NAFLD patients. The current diagnostic criteria of MS are more likely to 'capture' patients with NAFLD than with chronic hepatitis C, although both groups are insulin resistant.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".