Interactions Between Cytomegalovirus, Human Herpesvirus‐6, and the Recurrence of Hepatitis C After Liver Transplantation
Bibliographic record
Abstract
Recurrence of hepatitis C (HCV) following liver transplantation is common. Herpesvirus reactivation following transplant may have an immunomodulatory effect resulting in increased HCV replication. We studied whether cytomegalovirus (CMV) and human herpesvirus-6 (HHV-6) may be associated with HCV recurrence and viral load after transplant. We prospectively followed 66 HCV liver-transplant recipients with serial viral load testing for CMV and HHV-6. Infection and viral load were correlated with the development of biopsy-proven HCV recurrence and HCV viral loads. Histologic recurrence of HCV occurred in 41/66 (62.1%) patients. In the primary analysis, CMV infection and disease, and HHV-6 infection were not associated with HCV recurrence. Peak CMV and HHV-6 viral loads were not significantly different in patients with and without recurrence. No correlation was observed between HCV viral loads at 1 and 3 months post-transplant and peak HHV-6 or CMV viral loads. In a subgroup analysis, HHV-6 infection was associated with the development of more severe recurrence (hepatitis and/or fibrosis score > or = 2) (p = 0.01). Also, fibrosis scores at last follow up were higher in patients with CMV disease (1.67 vs. 0.56; p = 0.016) and in patients with HHV-6 infection (1.18 vs. 0.55; p = 0.031). In conclusion, HHV-6 and CMV infection and viral load were not associated with increased overall rates of HCV recurrence or HCV viral load after liver transplantation but may be associated with more severe forms of recurrence.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".