Emerging Role of Extracorporeal Support in Acute and Acute-on-Chronic Liver Failure: Recent Developments
Bibliographic record
Abstract
Acute liver failure (ALF) and acute-on-chronic liver failure (ACLF) are life-threatening illnesses requiring intensive care admission and potentially liver transplantation. Artificial extracorporeal liver support (ECLS) systems remove water-soluble and albumin-bound toxins to maintain normal serum chemistry, prevent further hepatic/organ system damage, and create an environment for potential hepatic regeneration/recovery (ALF) or bridge to liver transplantation (ALF and ACLF). Use of artificial ECLS has been studied in both ALF and ACLF. Artificial ECLS systems have been found to be safe and have demonstrated the following benefits: improvement of biochemistries, hemodynamic status, and hepatic encephalopathy. Despite this, only one prospective randomized controlled trial examining the use of high-volume plasma exchange has demonstrated improvement in transplant-free survival. Bioartificial (cell-based) ECLS systems build on the technology of artificial systems, incorporating living hepatocytes in a bioactive platform to further mimic endogenous hepatic detoxification and synthetic functions. Currently, no bioartificial system has been found to confer a mortality benefit; however, these platforms offer the greatest potential for future development.
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 | 0.001 |
| 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".