Rate of Infectious Complications during Interferon-Based Therapy for Hepatitis C Is Not Related to Neutropenia
Bibliographic record
Abstract
The relationship between infectious complications and neutropenia was evaluated in recipients of interferon-based therapy for hepatitis C followed at The Ottawa Hospital Viral Hepatitis Clinic from June 2000 to May 2005. One hundred ninety-two patients received 211 courses of therapy (5707 person-weeks of therapy). No patients received granulocyte colony-stimulating factor. Sixty-seven infectious complications occurred in 57 patients (1.17 infections per 100 person-weeks of therapy). The median time to infection was 17 weeks after the start of therapy. Age, sex, weight, race, human immunodeficiency virus status, stage and grade of biopsy, and type of interferon were not correlated with infection rate by Cox regression analysis. The rates of total, fungal, viral, and bacterial infections did not correlate with nadir neutrophil count or magnitude of decrease from baseline. Neutrophil count is not correlated with infection rate in recipients of interferon-based therapy for hepatitis C. Reduction in interferon dose and/or dosing with granulocyte colony-stimulating factor in those with neutropenia is not supported by this analysis.
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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".