Induction Versus Noninduction Antiviral Therapy for Chronic Hepatitis C Virus in Patients with Congenital Coagulation Disorders: A Canadian Multicentre Trial
Bibliographic record
Abstract
BACKGROUND: Patients with congenital coagulation disorders and chronic hepatitis C virus (HCV) infection have multiple risk factors (ie, infection predominantly with genotype-1 HCV, long duration of the disease, HIV coinfection and male sex) for poor response to antiviral therapy. The present study compared induction therapy with interferon-alpha (IFN-alpha)-2b with standard IFN-alpha2b therapy. Pegylated IFN was not available at the time that the study was initiated. PATIENTS AND METHODS: A randomized study was performed comparing the efficacy of traditional IFN-alpha2b therapy (group A -- three million units, three times weekly for 24 to 48 weeks) and daily ribavirin (1.0 g to 1.2 g according to weight for 24 to 48 weeks), with induction IFN-alpha2b therapy (group B -- three million units, daily for eight weeks followed by the same dose administered three times a week for a further 16 to 40 weeks) and daily ribavirin (same dose as above) in IFN-naive patients with congenital coagulation disorders and chronic HCV infection. RESULTS: Between 2000 and 2003, 54 HIV-negative patients were recruited and randomly assigned to group A or B (n=27 each). Both groups were comparable in terms of age, sex, ethnicity, body mass index, baseline HCV RNA titre, viral genotype, liver fibrosis stage and type of coagulation disorder. Induction therapy did not significantly alter sustained virological response rates (group A 50%, group B 50%; P=1.0). Multiple logistic regression analysis indicated that induction therapy did not benefit individuals with difficult-to-treat infection (ie, those infected with genotypes 1 and 4, or those with high baseline viral loads). CONCLUSIONS: There was no benefit with induction antiviral therapy for HCV infection in individuals with congenital coagulation disorders.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".