Guidelines for Perioperative Care for Liver Transplantation: Enhanced Recovery After Surgery (ERAS) Recommendations
Bibliographic record
Abstract
BACKGROUND: Enhanced Recovery After Surgery (ERAS) is a multimodal, evidence-based, program of care developed to minimize the response to surgical stress, associated with reduced perioperative morbidity and hospital stay. This study presents the specific ERAS Society recommendations for liver transplantation (LT) based on the best available evidence and on expert consensus. METHODS: PubMed and ClinicalTrials.gov were searched in April 2019 for published and ongoing randomized clinical trials on LT in the last 15 y. Studies were selected by 5 independent reviewers and were eligible if focusing on each validated ERAS item in the area of adult LT. An e-Delphi method was used with an extended interdisciplinary panel of experts to validate the final recommendations. RESULTS: Forty-three articles were included in the systematic review. A consensus was reached among experts after the second round. Patients should be screened for malnutrition and treated whenever possible. Prophylactic nasogastric intubation and prophylactic abdominal drainage may be omitted, and early extubation should be considered. Early oral intake, mobilization, and multimodal-balanced analgesia are recommended. CONCLUSIONS: The current ERAS recommendations were elaborated based on the best available evidence and endorsed by the e-Delphi method. Nevertheless, prospective studies need to confirm the clinical use of the suggested protocol.
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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 | 0.044 | 0.098 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.013 | 0.008 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".