Predictors of Significant Fibrosis in Chronic Hepatitis B Patients With Low Viremia
Bibliographic record
Abstract
BACKGROUND AND AIM: The data on the prevalence and predictors of significant fibrosis (≥F2, METAVIR) in chronic hepatitis B virus (HBV) patients with low viremia are limited. We aimed to assess both the prevalence predictors of ≥F2 fibrosis in hepatitis B envelope antigen-negative patients with HBV DNA <20,000 IU/mL. METHODS: Hepatitis B envelope antigen-negative patients (n=213) with mean HBV DNA <2000 IU/mL (n=97) and HBV DNA 2000 to 20,000 IU/mL (n=116) were included and all had liver biopsy. Variables significantly associated with ≥F2 fibrosis on an univariate analysis were included in a multivariate logistic regression model. RESULTS: Overall, 40 (18.8%) patients had ≥F2 fibrosis, with no difference between those with mean HBV DNA <2000 IU/mL (19.6%) compared with patients with HBV DNA of 2000 to 20,000 IU/mL (18.1%; P=0.782). Fibrosis ≥F2 was similar in patients with HBV DNA <2000 versus 2000 to 20,000 IU/mL in relation to varying alanine aminotransferase thresholds (P>0.05), and was less frequent in persistently normal alanine aminotransferase patients (13.6%) when compared with those with elevated or fluctuating levels (25.3%, P=0.030). Fewer patients under 40 years of age had ≥F2 fibrosis (12.5%) as compared with older ones (28.2%; P=0.004). Logistic regression analysis identified higher aspartate aminotransferase [odds ratio (OR), 6.21; 95% confidence interval (CI), 2.48-15.54; P<0.0001], lower albumin (OR, 0.86; 95% CI, 0.78-0.95; P=0.002), platelet count (OR, 0.99; 95% CI, 0.98-0.99; P=0.013), and age (OR, 1.05; 95% CI, 1.01-1.09; P=0.024) as independent predictors of significant fibrosis. CONCLUSIONS: A small but significant minority of HBV patients with low viremia harbor significant fibrosis, although its rate is not different in those with viremia above or below 2000 IU/mL. Our findings may guide in decisions regarding liver biopsy and treatment in this category of patients.
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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".