High incidence of allograft dysfunction in liver transplanted patients treated with pegylated-interferon alpha-2b and ribavirin for hepatitis C recurrence: possible de novo autoimmune hepatitis?: Table 1
Bibliographic record
Abstract
BACKGROUND: Interferon may trigger autoimmune disorders, including autoimmune hepatitis, in immunocompetent patients. To date, no such disorders have been described in liver transplanted patients. METHODS: 9 of 44 liver transplanted patients who had been receiving pegylated-interferon alpha-2b and ribavirin for at least 6 months for hepatitis C virus (HCV) recurrence, developed graft dysfunction despite on-treatment HCV-RNA clearance in all but one case. Laboratory, microbiological, imaging and histological evaluations were performed to identify the origin of graft dysfunction. The International Autoimmune Hepatitis scoring system was also applied. RESULTS: In all cases infections, anastomoses complications and rejection were excluded, whereas the autoimmune hepatitis score suggested a "probable autoimmune hepatitis" (score from 10 to 14). Three patients developed other definite autoimmune disorders (overlap anti-mitochondrial antibodies (AMA)-positive cholangitis, autoimmune thyroiditis and systemic lupus erythematosus, respectively). In all cases, pre-existing autoimmune hepatitis was excluded. Anti-lymphocyte antibodies in immunosuppressive induction treatment correlated with the development of the disorder, whereas the use of granulocyte colony-stimulating factor to treat interferon-induced neutropenia showed a protective role. Withdrawal of antiviral treatment and treatment with prednisone resulted in different outcomes (five remissions and four graft failures with two deaths). CONCLUSIONS: De novo autoimmune hepatitis should be considered in differential diagnosis along with rejection in liver transplanted patients developing graft dysfunction while on treatment with interferon.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".