Silymarin treatment of viral hepatitis: a systematic review
Bibliographic record
Abstract
Silymarin from the milk thistle herb (Silybum marianum) is used by many patients with chronic viral hepatitis, but its efficacy remains unknown. We performed a systematic review of silymarin for the treatment of chronic viral hepatitis B and C. An exhaustive search strategy identified 148 papers that studied silymarin compounds in liver disease. Of these, four trials included patients with hepatitis C, one included hepatitis B patients, and two, unspecified chronic viral hepatitis. However, only one trial exclusively studied patients with hepatitis C, and none involved patients with only hepatitis B. Silymarin treatment resulted in a decrease in serum transaminases compared with baseline in four studies, and compared with placebo in only one study. There is no evidence that silymarin affects viral load or improves liver histology in hepatitis B or C. No studies were found that investigated the use of silymarin concomitantly with interferon, nucleoside analogues, or other conventional treatments for hepatitis B or C. In conclusion, silymarin compounds likely decrease serum transaminases in patients with chronic viral hepatitis, but do not appear to affect viral load or liver histology. Nevertheless it may be worthwhile to determine its effects in conjunction with standard antiviral treatment.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".