Preliminary Single-Center Canadian Experience of Human Normothermic Ex Vivo Liver Perfusion: Results of a Clinical Trial
Bibliographic record
Abstract
After extensive experimentation, outcomes of a first clinical normothermic machine perfusion (NMP) liver trial in the United Kingdom demonstrated feasibility and clear safety, with improved liver function compared with standard static cold storage (SCS). We present a preliminary single-center North American experience using identical NMP technology. Ten donor liver grafts were procured, four (40%) from donation after circulatory death (DCD), of which nine were transplanted. One liver did not proceed because of a technical failure with portal cannulation and was discarded. Transplanted NMP grafts were matched 1:3 with transplanted SCS livers. Median NMP was 11.5 h (range 3.3-22.5 h) with one DCD liver perfused for 22.5 h. All transplanted livers functioned, and serum transaminases, bilirubin, international normalized ratio, and lactate levels corrected in NMP recipients similarly to controls. Graft survival at 30 days (primary outcome) was not statistically different between groups on an intent-to-treat basis (p = 0.25). Intensive care and hospital stays were significantly more prolonged in the NMP group. This preliminary experience demonstrates feasibility as well as potential technical risks of NMP in a North American setting and highlights a need for larger, randomized studies.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".