Bibliographic record
Abstract
All but about 10% of patients with chronic hepatitis C (CHC) (predominantly those infected with genotype 1) can respond to some degree to 'combination' therapy with interferon (IFN) and ribavirin. The slower the virological response to treatment, the less likely sustained viral clearance will take place. Many factors influence response to antiviral therapy; most cannot be reversed (e.g. sex, age, cirrhosis, genotype and viral load). A sustained viral clearance is considerably facilitated by compliance with full-dose therapy for the prescribed time. The potential cause(s) for non-response need(s) to be ascertained before attempting retreatment. The 10% of patients who are true 'null' responders may respond to the new specifically targeted antiviral therapies but whether the response can be sustained off-therapy is unclear. Adjunctive therapies may facilitate response to retreatment if intolerance to treatment leading to diminished or absent doses was problematic in the past. Retreatment with a long-acting IFN and an adequate ribavirin dose (15 mg/kg), but given for 72 weeks in prior relapsers following 48 weeks of treatment, will enhance sustained virological response (SVR) rates. No benefit is gained from changing one pegylated IFNalpha (PEG IFNalpha) to another unless the treatment duration is extended. Only alpha-interferons are effective. For those individuals who still fail to achieve SVR, recruitment to trials of new treatments should be encouraged particularly for those with advanced liver disease. Lifestyle modification may be appropriate in attempt to reduce the chance of complications of liver disease, namely hepatocellular carcinoma, by smoking cessation, eliminating obesity and increasing coffee consumption.
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 | 0.015 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".