Post-liver transplantation outcomes in acute-on-chronic liver failure: Impact of alcohol as a precipitant and etiology of chronic liver disease
Bibliographic record
Abstract
Acute-on-chronic liver failure (ACLF) has been associated with excellent post-liver transplant (LT) outcomes at 1 year; however, the impact of alcohol as ACLF precipitant, specifically alcohol-associated hepatitis (AH), and as etiology of chronic liver disease remains uncertain. This study aimed to assess the effect of alcohol as ACLF precipitant and chronic liver disease etiology (alcohol-associated liver disease vs. non-alcohol-associated liver disease) on posttransplant outcomes. We performed a retrospective study using the Multi-Organ Dysfunction and Evaluation for LT Consortium database and included 640 patients with ACLF who underwent LT across 15 transplant centers in North America. The primary outcome was 1-year posttransplant survival. We used logistic regression and Cox proportional hazards to compare posttransplant survival, mortality risk, and health care utilization, adjusting for age, ACLF grade, comorbid diabetes mellitus, chronic kidney disease, and HCC. The median follow-up from LT was 2.8 years (P25-P75, 2.2-5.5 y) for patients with AH-ACLF (n=42) and 3.1 years (P25-P75, 1.6-4.9 y) for patients without AH (n=598). No significant difference was observed in 1-year survival after LT in patients with AH-ACLF versus those without AH ( p =0.36). Patients with AH had significantly higher health care utilization evidenced by greater length of stay (28.5 vs. 19.0 d, p =0.004; adjusted linear estimate 16.89, 95% CI: 7.66-26.11, p <0.001), higher rates of rehabilitation placement (71.4% vs. 41.8%, p =0.002; adjusted odds ratio: 4.13, 95% CI: 2.04-8.89, p <0.001), and non-ambulatory status (39.0% vs. 21.0%, p =0.005; adjusted odds ratio: 4.54, 95% CI: 1.90-10.79, p <0.001). Compared with other etiologies, alcohol-associated liver disease was not associated with differences in 1-year mortality, mortality risk over time, or health care utilization, after excluding patients with AH as ACLF precipitant. While there were no differences in 1-year survival, AH-ACLF was associated with higher health care resource utilization compared with other ACLF precipitants. LT centers should ensure adequate resources are allocated for the management of these patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".