The Association Between Metabolic Dysfunction‐Associated Steatotic Liver Disease and Change in Liver Stiffness in Patients With Chronic Hepatitis B
Bibliographic record
Abstract
BACKGROUND AND AIMS: Metabolic dysfunction-associated steatotic liver disease (MASLD) is associated with an increased risk of liver-related events in patients with chronic hepatitis B (CHB), possibly by accelerating fibrosis progression. Therefore, we studied the influence of MASLD on liver stiffness measurement (LSM) kinetics in CHB patients. METHODS: We conducted a multicenter retrospective cohort study of CHB patients with at least two LSM with FibroScan. We studied the absolute change in LSM and the change in LSM stage from the first LSM to the most recent LSM among CHB patients with MASLD compared to patients without MASLD. RESULTS: We analysed 1055 CHB patients; 259 (28.0%) had MASLD. Patients with MASLD had a higher first and last LSM (6.1 vs. 5.2 kPa and 5.6 vs. 4.7 kPa, p < 0.001), were significantly less likely to achieve a decrease in LSM stage (52.8% vs. 74% p < 0.001) and were more likely to experience an increase in LSM stage (19.3% vs. 13.6%, p = 0.035) during follow-up. 417 (39.5%) patients initiated antiviral therapy (AVT) which was associated with a decline in LSM (p < 0.001). However, patients with MASLD who were treated were less likely to decrease in LSM stage (52.4% vs. 77.0%, p < 0.001) and were more likely to experience an increase in LSM stage (23.5% vs. 12.8%, p = 0.021) despite AVT. CONCLUSION: Presence of MASLD was independently associated with higher LSM in untreated CHB patients and with less decline in LSM after initiation of AVT. Furthermore, CHB patients with MASLD were more likely to experience an increase in LSM despite AVT.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".