ABO-incompatible liver transplantation for critically ill adult patients
Bibliographic record
Abstract
ABO incompatible (ABO-In) liver transplant remains a controversial solution to acute liver failure in adults. Adult liver recipients with acute liver failure or severely decompensated end-stage disease, intubated and/or in the intensive care unit, were grouped as ABO-In (n = 14), ABO-compatible (n = 29, ABO-C) and ABO-identical (n = 65, ABO-Id). ABO-In received quadruple immunosuppression with antibody-depleting induction agents (except two), calcineurin inhibitors, antimetabolites and steroids. No significant difference of patient and graft survivals was observed among ABO-In, ABO-C and ABO-Id: graft survivals were 64%, 62% and 67%, respectively, in 1 year and 56%, 54% and 60%, respectively, in 5 years; patient survivals 86%, 69% and 67%, respectively, in 1 year and 77%, 61% and 62%, respectively, in 5 years. Three ABO-In grafts were lost (one hyper-acute rejection and two hepatic artery thrombosis). Surgical and infectious complications were similarly distributed between groups, except the hepatic artery thrombosis, more frequent in ABO-In (2, 14%) than ABO-I (1, 1.5%, P < 0.05). In contrast to previous studies, no significant difference of patient and graft survivals could be observed among all ABO-compatibility settings. Our results suggest that ABO-incompatible transplants should be viewed as an important therapeutic option in adult patients with acute liver failure awaiting an emergency procedure.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".