Clinical Recommendations for the Use of Recombinant Human Erythropoietin in Patients with Hepatitis C Virus Being Treated with Ribavirin
Bibliographic record
Abstract
Today, combination antiviral therapy with pegylated interferon-alpha and ribavirin (RBV) allows many patients infected with hepatitis C virus (HCV) to achieve a sustained virological response, which is equivalent to cure. Data also support the clinical benefit of combination antiviral therapy in patients coinfected with HCV and HIV, and in patients who have received a liver transplant. Antiviral therapy with pegylated interferon-alpha and RBV is, however, associated with a high incidence and significant magnitude of anemia. This anemia may have several mechanisms, including bone marrow suppression and hemolysis. In addition, patients coinfected with HIV may have both pre-existing and RBV-associated anemia. Management of anemia in patients with HCV through RBV dose reduction or treatment discontinuation may compromise the effectiveness of treatment, because studies have demonstrated that treatment adherence or maintenance of antiviral therapy dose is an important predictor of sustained virological response. Anemia associated with combination antiviral therapy in patients with HCV is frequently associated with an inadequate or blunted endogenous erythropoietin response. Accumulating evidence now supports the use of recombinant human erythropoietin (rHuEpo) to manage anemia in these patients, with the objective of maintaining the RBV dose, but clinical standards are lacking. The present article reviews the data relevant to the use of rHuEpo in this patient population and proposes a set of clinical practice standards to assist clinicians in selecting patients for rHuEpo and in implementing rHuEpo therapy effectively.
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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 | 0.010 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.017 | 0.011 |
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".