Surgical and Interventional Radiology Management of Vascular and Biliary Complications in Liver Transplantation: Narrative Review
Bibliographic record
Abstract
Abstract Liver transplant patients require a multidisciplinary and personalized approach to optimize outcomes. Posttransplant complications can be devastating for the patient and can jeopardize graft survival. Therefore, a careful evaluation and stepwise decision-making process is necessary to determine the best strategy, whether it is surgical, interventional, or a combination of both. While access to liver transplant interventions in Latin America can be more limited compared with other parts of the world, many countries in the region have made significant progress in developing their liver transplant programs and improving the management of posttransplant complications. For example, in Brazil, specialized transplant centers and multidisciplinary teams have been established to reduce morbidity and improve graft survival rates. The article also explores the latest advancements in interventional radiology techniques, such as angioplasty, stent placement, and embolization, and how they can be used to successfully treat these complications. Overall, this article highlights the importance of a comprehensive approach to managing complications in liver transplant patients and emphasizes how individualized treatment plans can lead to improved outcomes, even in settings with limited resources.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".