Perihepatic lymph nodes as markers of disease response in patients with hepatitis C-related liver disease: a prospective clinical evaluation
Bibliographic record
Abstract
AIM: To assess the clinical feasibility of utilizing the presence of perihepatic lymphadenopathy, seen on ultrasound, as a marker of response to antiviral treatment in patients with hepatitis C virus (HCV)-related liver disease. METHODS: Eighty-five patients with HCV-related liver disease [51 men and 34 women; mean age 47 years (range 26-67)] underwent liver biopsy and baseline ultrasound scans. Twenty-two of these patients were followed up longitudinally with 6-monthly ultrasound scans, whereas they were receiving anti-HCV eradication therapy with interferon and ribavirin. Perihepatic lymph nodes detected in the coeliac axis and peripancreatic region were noted, with the largest node size on maximal diameter recorded. The patients were subsequently assessed in the light of long-term virological response to treatment. RESULTS: Perihepatic lymph nodes were detected in 26 of the 85 patients. Of the 22 patients followed up longitudinally, 11 responded to antiviral treatment, nine failed to respond and two did not complete a course of treatment. No significant difference was found between patients with detectable lymphadenopathy and those without according to age, sex, disease severity and genotype. There was a general reduction in size of lymph nodes in both responders and nonresponders to treatment, although this reduction was only significant in the responder group (P=0.003). CONCLUSION: The presence of perihepatic lymphadenopathy when detected in patients with viral hepatitis can potentially serve as an indicator of response to treatment. However, as only 30-40% of patients have detectable lymphadenopathy, its clinical utility is limited.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".