Avoiding ICU Admission by Using a Fast-Track Protocol Is Safe in Selected Adult-to-Adult Live Donor Liver Transplant Recipients
Bibliographic record
Abstract
Background We evaluated patient characteristics of live donor liver transplant (LDLT) recipients undergoing a fast-track protocol without intensive care unit (ICU) admission versus LDLT patients receiving posttransplant ICU care. Methods Of the 153 LDLT recipients, 46 patients were included in our fast-track protocol without ICU admission. Both, fast-tracked patients and ICU-admitted patients were compared regarding donor and patient characteristics, perioperative characteristics, and postoperative outcomes and complications. In a subgroup analysis, we compared fast-tracked patients with patients who were admitted in the ICU for less than 24 hours. Results Fast-tracked versus ICU patients had a lower model for end-stage liver disease score (13 ± 4 vs 18 ± 7; P < 0.0001), lower preoperative bilirubin levels (51 ± 50 μmol/L vs 119.4 ± 137.3 μmol/L; P < 0.001), required fewer units of packed red blood cells (1.7 ± 1.78 vs 4.4 ± 4; P < 0.0001), and less fresh-frozen plasma (2.7 ± 2 vs 5.8 ± 5; P < 0.0001) during transplantation. Regarding postoperative outcomes, fast-tracked patients presented fewer bacterial infections within 30 days (6.5% [3] vs 29% [28]; P = 0.002), no episodes of pneumonia (0% vs 11.3% [11]; P = 0.02), and less biliary complications within the first year (6% [3] vs 26% [25]; P = 0.001). Also, fast-tracked patients had a shorter posttransplant hospital stay (10.8 ± 5 vs 21.3 ± 29; P = 0.002). In the subgroup analysis, fast-tracked vs ICU patients admitted for less than 24 hours had lower requirements of packed red blood cells (1.7 ± 1.78 vs 3.9 ± 4; P = 0.001) and fresh-frozen plasma (2.7 ± 2 vs 5.8 ± 4.5; P = 0.0001). Conclusions Fast-track of selected patients after LDLT is safe and feasible. An objective score to perioperatively select LDLT recipients amenable to fast track is yet to be determined.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".