Chronic hepatitis C in patients with HIV/AIDS: a new challenge in antiviral therapy
Bibliographic record
Abstract
HIV-infected patients are living longer since the introduction of highly active antiretroviral therapy. However, coinfection with the hepatitis C virus (HCV) leads to increased morbidity from liver disease and higher overall mortality. The prevalence of chronic hepatitis C among patients with HIV/AIDS ranges from 7% (sexual transmission of HIV) to >90% (injection drug use). Uncontrolled HIV infection seems to accelerate the progression of HCV-induced liver fibrosis. Forty-eight weeks of combination therapy with pegylated interferon alpha (2a or 2b) plus ribavirin achieves a sustained viral response in coinfected individuals in up to 38% with HCV genotype 1 and up to 73% with genotypes 2 or 3. The safety profile of this treatment is similar to therapy in HCV-monoinfected patients with influenza-like symptoms, cytopenia and neuropsychiatric symptoms dominating. However, HIV/HCV-coinfected patients who also take zidovudine develop more profound anaemia than those on other HIV nucleoside analogue therapy. Didanosine and stavudine are associated with rare but serious mitochondrial toxicity, such as pancreatitis or lactic acidosis. It does not appear that the addition of ribavirin increases that risk. There is currently no evidence that in HIV/HCV coinfection one pegylated interferon product is superior to the other. Contrary to common perception, it is also unproven that HIV/HCV-coinfected patients respond less well to therapy with peginterferon alpha plus ribavirin than HCV-monoinfected patients. Given the safety and efficacy of combination therapy with peginterferon plus ribavirin and the deleterious effects of chronic hepatitis C, all HIV/HCV-coinfected patients should be evaluated for therapy.
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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 | 0.013 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.011 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".