Histopathological Features Predicting Long-term Clinical Outcomes in Patients with Vanishing Bile Duct Syndrome
Bibliographic record
Abstract
Background and Aims: The clinicopathological features and long-term outcomes of patients with vanishing bile duct syndrome (VBDS) have yet to be elucidated. The study aims to investigate these features and identify factors associated with poor prognosis. Methods: This multicenter retrospective study recruited patients with liver biopsy-proven VBDS who were followed up at five hospitals in northern China from January 2003 to April 2022. Clinical and pathological data at time of biopsy were reviewed. Clinical outcomes including cirrhosis, decompensation events, liver transplantation (LT), and liver-related death were recorded. Cox regression analysis was used to identify the risk factors associated with poor outcomes. Results: A total of 183 patients were included. The median age was 47 years, with 77.6% being women. During a median follow-up of 4.8 years, 88 patients developed compensated or decompensated cirrhosis, 27 died, and 15 received LT. Multivariate Cox regression analysis showed that hepatocellular cholestasis (HR 2.953, 95% CI: 1.437-6.069), foam cells (HR 2.349, 95% CI: 1.092-5.053), and advanced fibrosis (HR 2.524, 95% CI: 1.313-4.851) were independent predictors of LT or liver-related deaths. A nomogram formulated with the above factors showed good consistency with a concordance index of 0.746 (95% CI: 0.706-0.785). Conclusions: Nearly half of VBDS patients studied progressed to end-stage liver disease and 23% of them had LT or liver-related death within two years of diagnosis. Hepatocellular cholestasis, foam cells and advanced fibrosis rather than the degree of bile duct loss or underlying etiologies were independently associated with poor prognosis in VBDS patients.
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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 | 0.000 | 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".