Bibliographic record
Abstract
Orthotopic liver transplantation is the only definitive treatment for end-stage liver disease. More than 6000 procedures are performed in the United States annually with excellent survival rates. The shortage of donor organs leads to continued interest in techniques to enlarge the potential donor pool. Patients presenting for liver transplant suffer from important cardiovascular, respiratory, renal, neurological, and gastroenterological comorbidity. In the Western world, liver failure is increasingly caused by steatohepatitis, and transplant candidates are thus becoming older and more comorbid. The role of the transplant anesthesiologist is highly important in the preoperative assessment, intraoperative management, and postoperative care of these complex and sick patients. Appropriate investigation and management of comorbidities such as coronary artery disease and portopulmonary hypertension is controversial and differs between programs. The transplant procedure is a major surgery, and although massive transfusion is no longer commonplace, there is potential for significant hemodynamic instability, coagulopathy, and metabolic disturbance. Liver transplant surgery can be divided into the preanhepatic phase, the anhepatic phase, and the reperfusion phase, with important anesthetic considerations at each point. An understanding of the surgical techniques used for vascular exclusion of the liver and the role of venovenous bypass is crucial for the anesthesiologist. Recent trends in perioperative care include the use of antifibrinolytic drugs and point-of-care coagulation tests, intraoperative renal replacement therapy, and "fast-track" extubation and postoperative care. Care of patients with fulminant hepatic failure or those receiving split-liver grafts requires special consideration.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.058 | 0.027 |
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".