Ex-Vivo Lung Perfusion: From Bench to Bedside
Bibliographic record
Abstract
Lung transplantation is an established treatment option for eligible patients with end-stage lung disease. Nonetheless, there exists an imbalance between donor lungs considered suitable for transplantation and the ever-growing number of patients dying on the waiting list. This chapter reflects the potential alternative, normothermic ex-vivo lung perfusion (EVLP), which has emerged to address this issue and how it can expand the currently limited donor pool. Normothermic ex-vivo lung perfusion (EVLP), as a novel preservation technique, is capable of assessing, evaluating, and improving lung function prior to lung transplantation. Here, we (1) contrast the various available commercial EVLP available and used around the world; (2) outline the University of Alberta novel EVLP circuit; (3) discuss the limitations present between clinical and laboratory applications; and (4) present what we are currently working on at the laboratory to further improve the assessment techniques used on EVLP.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".