Hepatitis B Virus Variants and Cytokine Patterns in Acute Liver Failure and Transplant‐Free Survival
Bibliographic record
Abstract
ABSTRACT Background & Aims Only 25% of hepatitis B‐related acute liver failure (HBV‐ALF) patients survive without liver transplantation (transplant‐free survival, TFS). There is limited study of immunological and virological profiles in these patients. We analysed the association between hepatitis B viremia and cytokine patterns on TFS of HBV‐ALF patients. Methods We identified 48 acute and 20 history of HBV infection ALF patients from the US ALF Study Group registry (> 3400 patients). The inclusion criteria were age > 18 years, diagnosis of HBV‐ALF with hepatic encephalopathy and INR ≥ 1.5. Data were collected from ICU admission through day 21. Serum collected at admission and at days 3–5 were used for cytokine quantification by Luminex and novel HBV biomarkers, genotypes and variants. Results In 48 acute (50% F, median age 40 years) and 20 history/reactivation (40% F, median age 53 years) HBV‐ALF patients, there were 26 (54%) and 5 (25%) TFS, respectively. Detectable HBV DNA by clinical PCR assay (median 3.39 log 10 IU/mL, aOR 5.308; 95% CI: 1.217–23.155, p = 0.026) and qAHBc levels (median 4.5 log 10 IU/mL, aOR 4.466, 95% CI: 0.968–20.608, p = 0.050) were associated with TFS in acute HBV‐ALF patients. HBV variants associated with anti‐viral immune escape were more frequently detected in acute HBV‐ALF TFS patients compared to non‐TFS ( p < 0.05). TFS with acute HBV‐ALF had higher angiogenic factors (PDGF‐AA, p = 0.008; PDGF‐BB, p = 0.0006; VEGF‐A, p = 0.014) and lower pro‐inflammatory cytokine levels (IL‐1α, p = 0.031; IL‐2, p = 0.014; IL‐6, p = 0.039). Significant differences in HBV viremia were not observed in history/reactivation of HBV‐ALF patients. Conclusions Acute HBV‐ALF patients with TFS were often viremic with immune escape variants, increased angiogenic factors and decreased pro‐inflammatory cytokines. Trial Registration: ClinicalTrials.gov identifier: NCT00518440
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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 | 0.002 |
| 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) | 0.002 | 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".