Risk factors for anaemia in human immunodeficiency virus/hepatitis C virus‐coinfected patients treated with interferon plus ribavirin
Bibliographic record
Abstract
The most frequent and the most troublesome adverse effect of interferon plus ribavirin-based therapy is anaemia. The aim of this analysis was to determine the incidence and risk factors of anaemia (Hb < 10 g/dL) in human immunodeficiency virus/hepatitis C virus (HCV)-coinfected patients receiving anti-HCV therapy. We reviewed all cases of anaemia occurring among 416 patients participating in a randomized, controlled 48-week trial comparing peginterferon (peg-IFN) alpha 2b plus ribavirin with interferon alpha-2b plus ribavirin. Univariate and multivariate analyses were used to identify links with antiretroviral treatments, HCV therapy and clinical and laboratory findings. Sixty-one (15.9%) of the 383 patients who received at least one dose of anti-HCV treatment developed anaemia. In multivariate analysis the risk of anaemia was significantly associated with zidovudine (OR, 3.27 95% CI, 1.64-6.54, P = 0.0008) and peg-IFN (OR, 2.35; 95% CI, 1.16-4.57, P = 0.0179). The risk of anaemia was lower in patients with higher baseline haemoglobin levels (OR, 0.35 95% CI, 0.26-0.49, P < 0.0001) and in patients receiving protease inhibitor-based antiretroviral therapy (OR, 0.51 95% CI, 0.30-0.86, P = 0.0114). Zidovudine discontinuation could help to avoid anaemia associated with anti-HCV therapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".