Future directions in acute liver failure
Bibliographic record
Abstract
Acute liver failure (ALF) describes a clinical syndrome of rapid hepatocyte injury leading to liver failure manifested by coagulopathy and encephalopathy in the absence of pre-existing cirrhosis. The hallmark diagnostic features are a prolonged prothrombin time (ie, an international normalized ratio of prothrombin time of ≥1.5) and any degree of mental status alteration (HE). As a rare, orphan disease, it seemed an obvious target for a multicenter network. The Acute Liver Failure Study Group (ALFSG) began in 1997 to more thoroughly study and understand the causes, natural history, and management of ALF. Over the course of 22 years, 3364 adult patients were enrolled in the study registry (2614 ALF and 857 acute liver injury-international normalized ratio 2.0 but no encephalopathy-ALI) and >150,000 biosamples collected, including serum, plasma, urine, DNA, and liver tissue. Within the Registry study sites, 4 prospective substudies were conducted and published, 2 interventional ( N -acetylcysteine and ornithine phenylacetate), 1 prognostic [ 13 C-methacetin breath test (MBT)], and 1 mechanistic (rotational thromboelastometry). To review ALFSG's accomplishments and consider next steps, a 2-day in-person conference was held at UT Southwestern Medical Center, Dallas, TX, entitled "Acute Liver Failure: Science and Practice," in May 2022. To summarize the important findings in the field, this review highlights the current state of understanding of ALF and, more importantly, asks what further studies are needed to improve our understanding of the pathogenesis, natural history, and management of this unique and dramatic condition.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.021 | 0.007 |
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".