The Interaction among Insulin Resistance, Liver Fibrosis and Early Virological Response in Egyptian Patients with Chronic Hepatitis C
Bibliographic record
Abstract
BACKGROUND: Hepatitis C virus (HCV) infection may induce insulin resistance (IR) irrespective of the severity of liver disease, and there is evidence of a central role for IR in failure to achieve sustained virological response (SVR) in HCV patients. OBJECTIVE: To assess IR as a predictor of the severity of hepatic fibrosis in Egyptian HCV patients, and its effect on early viral kinetics and virological response to HCV therapy. METHODS: A total of 140 chronic HCV patients were divided into two groups according to the homeostasis model assessment-IR (HOMA-IR). Group 1 consisted of 48 chronic HCV patients with HOMA-IR >=2, and group 2 consisted of 92 chronic HVC patients without IR (HOMA IR <2). All patients were treated with combination therapy (pegylated interferon-alpha 2a plus ribavirin) for 48 weeks and studied for viral kinetics throughout the period of therapy. RESULTS: The study revealed that older age, higher body mass index and HOMA-IR >=2 were significantly associated with advanced fibrosis. Rapid virological response, complete early virological response and SVR were significantly lower in the IR-HCV group compared with the non-IR-HCV group. Univariate and multivariate analyses revealed that older age, fibrosis (F>=3), high viral load (>600,000 IU⁄mL) and HOMA-IR >=2 were significantly associated with a lack of viral kinetics as well as SVR. However, HOMA-IR >=2 was the main independent variable associated with lack of SVR. On the other hand, body mass index, plasma insulin level and HOMA-IR decreased significantly compared with starting levels in patients who achieved SVR. This suggests a cause and effect relationship between HCV infection and IR. CONCLUSION: IR in chronic HCV patients is associated with progressive fibrosis and slow viral kinetics, and could be a predictor for lack of rapid and early virological response. Therefore, HOMA-IR levels should be measured and improved before starting antiviral treatment.
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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 | 0.000 |
| 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".