Advances in management and prognostication in critically ill cirrhotic patients
Bibliographic record
Abstract
PURPOSE OF REVIEW: To provide an update on the recent publications for the management and prognostication of critically ill cirrhotic patients before and after liver transplant. RECENT FINDINGS: The CLIF Acute-oN-ChrONicLIver Failure in Cirrhosis (CANONIC) study recently derived an evidence-based definition of acute-on-chronic liver failure (ACLF): hepatic decompensation; organ failure [predefined by the Chronic Liver Failure-Sequential Organ Failure Assessment (CLIF-SOFA)]; and high 28-day mortality rate. Although Sequential Organ Failure Assessment (SOFA) appears to be more accurate in predicting ICU and hospital mortality in ACLF patients, CLIF-SOFA has been derived specifically for critically ill cirrhotic patients, including those not receiving mechanical ventilation. Recent data suggest that a lower transfusion target in esophageal variceal bleeding (<7 g/l) is safe. Newly defined 'cirrhosis-associated acute kidney injury (AKI)' correlates with mortality, organ failure and length of hospital stay. Although the SOFA score appears to perform better than liver-specific scoring systems [Model for End-stage Liver Disease (MELD) and Child-Pugh scores], neither MELD nor SOFA appears to independently predict posttransplant survival; however, correlated with lengths of ICU and hospital stay. For patients declined for liver transplant, palliative care referral and appropriate goals of care are rarely achieved. SUMMARY: New definitions for ACLF, cirrhosis-associated AKI and the CLIF-SOFA may improve the discrimination between survivors and nonsurvivors with ACLF. Predicting futility postliver transplant based on preliver transplant severity of illness still poses significant challenges.
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 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 | 0.000 | 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 | 0.000 |
| 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".