Autoimmune forms of chronic hepatitis associated with hepatitis C virus (HCV) infection with and without HCV‐RNA: Histological differences from pure autoimmune hepatitis and chronic hepatitis C
Bibliographic record
Abstract
Liver biopsy specimens of pure autoimmune hepatitis (pAIH), autoimmune forms of chronic hepatitis with positivity for anti-hepatitis C virus (anti-HCV) and negativity for HCV-RNA (cAIH-RNA(-)), autoimmune forms of chronic hepatitis with positivity for anti-HCV and HCV-RNA (cAIH-RNA(+)), and chronic hepatitis C (CHC) were compared histologically and statistically to clarify the histological character of the autoimmune form of chronic hepatitis with HCV infection. The following representative histological features were used to investigate: inflammation, fibrosis, plasma cell infiltration, lymphoid aggregates/follicles, non-suppurative destructive cholangitis, and the shape of the enlarged portal tracts. While a considerable overlap in histological features between the pAIH and cAIH-RNA(-) groups and between the CHC and cAIH-RNA(+) groups was recognized, the overlap between the pAIH and CHC groups was small. Significant differences were found between cAIH-RNA(-) and cAIH-RAN(+) groups, especially in necroinflammatory findings. In conclusion, most cases of cAIH-RNA(-) with histological features similar to those of pAIH were shown to be AIH. The remaining cases might be CHC with subsidence of viral duplication. Conversely, many cases of cAIH-RNA(+) with histological findings similar to those of CHC were shown to be CHC clinically mimicking pAIH. The remaining cases might represent coexistence of pAIH and HCV infection.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".