Epidemiology and Treatment of Hepatitis C Genotypes 5 and 6
Bibliographic record
Abstract
Chronic hepatitis C infection is a major global health problem. The WHO estimates the number of infected people worldwide to be approximately 170 million. The estimated number of hepatitis C virus (HCV)-infected people in Canada is approximately 250,000, with approximately 5000 Canadians newly infected each year. Based on the identification of genomic differences, HCV has been classified into six genotypes; genotype may influence the outcome of antiviral therapy. HCV genotypes 1, 2 and 3 are widely distributed throughout the world and have been the focus of the majority of epidemiological, natural course and treatment studies. Although HCV genotypes 5 and 6 are prevalent in certain geographical areas, they are studied less extensively. HCV genotypes 5 and 6 are uncommon in Canada and account for less than 5% of HCV-infected Canadians. However, immigration and travel can alter the epidemiology of these uncommon genotypes. The present article reviews and summarizes the available data regarding the epidemiology and treatment of HCV genotypes 5 and 6. Genotype 5 is endemic in the northern part of South Africa while genotype 6 is reported primarily in Asia. Available data show that 48 weeks of treatment with a combination of pegylated interferon and ribavirin lead to a higher sustained virological response compared with HCV genotypes 1 and 4. None of the approved direct-acting antiviral agents is currently recommended for the treatment of HCV genotypes 5 or 6.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".