Coagulopathy and hemostasis management in patients undergoing liver transplantation
Bibliographic record
Abstract
Patients with acute and chronic liver disease present with a wide range of disease states and severity that may require liver transplantation (LT). Physiologic alterations occur that are dynamic throughout all phases of perioperative care, creating complex management scenarios that necessitate multidisciplinary clinical care. Specifically, alterations in hemostasis in liver disease can be pronounced and evolve with disease progression over time. Recent studies and society guidance address this emerging paradigm and offer recommendations to assist with hemostatic management in patients with liver disease. However, patients undergoing LT are unique and diverse, often with unstable disease that requires specialized approaches. Our aim is to provide a focused review of hemostatic management of the LT patient, distinguish unique aspects of the three main phases of care (before LT, perioperative, and after LT), and identify knowledge gaps and critical areas of future research.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".