Preventing Small-for-size Syndrome in Living Donor Liver Transplantation: Guidelines From the ILTS-iLDLT-LTSI Consensus Conference
Bibliographic record
Abstract
Small-for-size syndrome (SFSS) is a well-recognized complication following liver transplantation (LT), with up to 20% developing this following living donor LT (LDLT). Preventing SFSS involves consideration of factors before the surgical procedure, including donor and recipient selection, and factors during the surgical procedure, including adequate outflow reconstruction, graft portal inflow modulation, and management of portosystemic shunts. International Liver Transplantation Society, International Living Donor Liver Transplantation Group, and Liver Transplant Society of India Consensus Conference was convened in January 2023 to develop recommendations for the prediction and management of SFSS in LDLT. The format of the conference was based on the Grading of Recommendations, Assessment, Development, and Evaluation system. International experts in this field were allocated to 4 working groups (diagnosis, prevention, anesthesia, and critical care considerations, and management of established SFSS). The working groups prepared evidence-based recommendations to answer-specific questions considering the currently available literature. The working group members, independent panel, and conference attendees served as jury to edit and confirm the final recommendations presented at the end of the conference by each working group separately. This report presents the final statements and evidence-based recommendations provided by working group 2 that can be implemented to prevent SFSS in LDLT patients.
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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 | 0.001 | 0.000 |
| 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) | 0.000 | 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".