Severity and Outcome of Acute-on-Chronic Liver Failure is Dependent on the Etiology of Acute Hepatic Insults
Bibliographic record
Abstract
BACKGROUND: Acute-on-chronic liver failure (ACLF) may be precipitated by various hepatic insults. The present study evaluated the outcomes of ACLF with different acute insults. PATIENTS AND METHODS: A total of 368 ACLF patients were included. Data collected included etiologies of acute hepatic insult and underlying chronic liver disease, and organ failure. Model for end-stage liver disease (MELD), chronic liver failure consortium (CLIF)-C ACLF, and acute physiology and chronic health evaluation (APACHE) II scores were calculated. Predictors of survival were assessed by the Cox proportional hazard model. RESULTS: The most frequent acute insult was active alcohol consumption [150 (40.8%) patients], followed by hepatitis B virus (HBV) [71 (19.3%) patients], hepatitis E virus (HEV) superinfection [45 (12.2%) patients], autoimmune hepatitis flare [17 (4.6%) patients], antituberculosis drugs [16 (4.3%) patients], and hepatitis A virus superinfection [2 (0.5%) patients]; 67 (18.2%) cases were cryptogenic. Alcohol-ACLF and cryptogenic-ACLF were more severe. Median CLIF-C, MELD, and APACHE II scores in alcohol-ACLF and cryptogenic-ACLF were significantly higher than those in HBV-ACLF and HEV-ACLF (CLIF-C: 47.1, 47.4 vs. 42.9, 42.0, P=0.002; MELD: 29, 29.9 vs. 28.9, 25.2, P=0.02; APACHE II: 16.5, 18.0 vs. 12, 14, P<0.001, respectively). Frequencies of kidney and brain failures were also higher in alcohol/cryptogenic-ACLF than in HBV/HEV-ACLF (kidney failure: 35.3%/34.3% vs. 23.9%/11.1%, P=0.009; brain failure: 26.0%/22.4% vs. 15.5%/4.4%, P=0.01, respectively). Mortality in the alcohol-ACLF group was the highest (64.0%), followed by that in the cryptogenic-ACLF (62.7%), HBV-ACLF (45.1%), and HEV-ACLF (17.8%) groups (P<0.001). In multivariable analysis, alcohol-ACLF had significantly higher mortality compared with HEV-ACLF (hazard ratio, 3.06; 95% confidence interval, 1.10-8.49, P=0.03). CONCLUSIONS: Alcohol/cryptogenic-ACLF had more severe phenotypic presentation, more incidence of organ failures, and higher mortality compared with HEV/HBV-ACLF. Alcohol-ACLF had the highest mortality, whereas HEV-ACLF had the best survival.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".