Fast relapse and high drop out rate of 48 weeks daily interferon monotherapy in HIV-infected patients with chronic hepatitis C
Bibliographic record
Abstract
BACKGROUND: The standard of care for HCV Hepatitis is the combination of interferon (IFN) plus Ribavirin. In HIV patients the use of this combination therapy may induce drug interactions, and reduces the adherence to HAART. The aim of this study is to evaluate safety and efficacy of a 48 weeks daily dose IFN schedule. METHODS: We evaluated 50 coinfected patients; alpha IFN 2a was administered at a dose of 3 MU daily. The baseline values were the following : CD4+ 515 cells/mmc (mean); HIV-RNA <50 copies/ml in all patients; HCV-RNA 28, 3 x 106 copies/ml. RESULTS: At 48 weeks, 10 patients (20%) achieved a biochemical and virological response according to an intention to treat analysis.Twenty four patients (48%) underwent a drop-out mainly by side effects related to overlapping toxicity of interferon and antiretroviral therapy. All the patients, who responded to the treatment, showed a fast relapse one month after the end of treatment. CONCLUSION: Although our results demonstrated a very poor outcome and a bad tolerance to interferon monotherapy, this approach should not be dropped out, mainly in patients at high risk for side effects and in those with cirrhosis who do not tolerate or are at increased risk for the use of ribavirin.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".