Direct‐Acting Antiviral Treatment of Patients with Hepatitis C Resolves Serologic and Histopathologic Features of Autoimmune Hepatitis
Bibliographic record
Abstract
Patients with hepatitis C virus (HCV) often have elevated serum markers and histologic features of autoimmune hepatitis (AIH). We evaluated an HCV‐positive (HCV+) study group that had elevated serum markers of AIH before starting direct‐acting antiviral (DAA) therapy (n = 21) and compared them to an HCV+ control group that did not have laboratory studies suggesting AIH (n = 21). Several patients in the study (17/21) and control (11/21) groups had liver biopsies before DAA treatment, and many were biopsied due to elevated serum markers of AIH. Evaluation of pre‐DAA treatment liver biopsies showed histologic features suggestive of AIH in 64.7% (11/17) of the study group and 45.5% (5/11) of the control group. Patients who were HCV+ with elevated serum markers of AIH had significantly increased hepatitis activity (P < 0.001) and slightly increased fibrosis stages (P = 0.039) in their pretreatment liver biopsies compared to controls. We hypothesized that the elevated serum markers and histologic features of AIH would resolve following DAA treatment. Serum markers of AIH in the study group began decreasing by 6 months posttreatment, and 52.4% (11/21) had complete resolution. Alanine aminotransferase levels significantly decreased into the normal range for all patients (21/21). Even patients that had persistence of serum markers of AIH after DAA treatment had normal transaminases. Six patients from the study patient group and 4 patients from the control group had follow‐up liver biopsies after DAA treatment, and all biopsies showed resolution of the histologic features of AIH.Conclusion: The majority of HCV+ patients that have serum markers and/or histopathologic features of AIH should initially be treated with DAA.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".