Improvement in Survival After Transplantation for Critically Ill Patients With Cirrhosis in the United States
Bibliographic record
Abstract
INTRODUCTION: There is considerable debate over the indication of liver transplantation (LT) for critically ill patients with cirrhosis, in part due to their potentially poor post-LT prognosis. We analyzed the epidemiology and outcome of LT for critically ill patients with cirrhosis over 4 time periods of 4 years. METHODS: We included adult patients who underwent liver transplant alone between 2005 and 2020 using the United Network for Organ Sharing registry database. We defined critically ill patients with cirrhosis as being in the intensive care unit with 1 or more of the following characteristics at the time of LT: (i) grade III/IV hepatic encephalopathy, (ii) mechanical ventilation, (iii) dialysis, and (iv) vasopressors. RESULTS: A total of 85,594 LT recipients were included, 5,827 (6.8%) of whom were classified as being critically ill with cirrhosis at the time of LT. The number and percentage of critically ill LT recipients with cirrhosis increased over the study period: 819 (4.3%) in 2005-2008 vs 2,067 (7.9%) in 2017-2020, P < 0.001. There was a 17% absolute increase in 1-year survival after LT: 72.5% in 2005-2008 vs 89.5% in 2017-2020, P < 0.001. The 1-year post-LT survival gap between critically ill and noncritically ill patients with cirrhosis narrowed over the study period: 16.7 percentage points in 2005-2008 vs 4.6 percentage points in 2017-2020. The year of LT was independently associated with lower 1-year post-LT mortality (hazard ratio 0.92, 95% confidence interval 0.91-0.93, P < 0.001). DISCUSSION: The absolute number and relative percentage of LT recipients who were critically ill increased over time, as did 1-year post-LT survival. Meanwhile, the gap in survival between this group of patients and noncritically ill patients with cirrhosis decreased but persisted. Cautious access to selected LT candidates who are critically ill may be warranted, provided the gap in survival with noncritically ill patients remains as small as possible.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".