Marginal Donor Utilization from Exceptional Geographic Distance after Ex-Vivo Lung Perfusion
Bibliographic record
Abstract
Introduction Lung transplantation remains the only treatment for advanced end-stage lung disease from a variety of etiologies. A profound lack of donor organs remains the greatest challenge in providing lung transplantation. The use of marginal donors is one strategy to expand the donor pool, complemented using technology such as ex-vivo lung perfusion (EVLP). The exceptionally large geographic distances and relative isolation of transplant centres in Canada remains a barrier to effective organ utilization. Case Description A 56-year-old male from a remote location with end-stage chronic obstructive pulmonary disease had recently deteriorated and was in imminent need of mechanical ventilation. The donor lungs were procured from a 70-year-old male over 3,700 km away. Due to the vast distances separating the donor, recipient and our centre, the recipient became stuck in-transit while the donor organs had already been cross-clamped. We decided to utilize EVLP in the hopes of preserving the organs and allowing for serial evaluation while the recipient was in-transit. EVLP was performed for 345-minutes upon arrival at our centre. During that time, hemodynamic parameters remained stable, compliance was excellent and a P/F ratio of 386 was achieved. The implantation was performed on cardiopulmonary bypass. The left lung time outside the body was 966-minutes, while the right lung time outside the body was 1033-minutes. It was obvious the lungs had sustained a massive ischemia-reperfusion injury, with copious amounts of transudative pulmonary edema flooding the endotracheal tube and chest tubes. This improved after re-exploration and aggressive fluid resuscitation. The patient made a slow, but complete recovery and was transferred back to his home hospital after 38-days. The recipient continues to function well at home 8-months post-transplantation. Conclusion This case report highlights the challenges faced by geographically isolated transplantation centres, resulting in prolonged ischemic times and acceptance of marginal donors, and the utility of EVLP to objectively evaluate and potentially ameliorate ischemic damage. Even though these donor lungs were labelled as marginal due to advanced donor age, the recipient recovered well and is now thriving at home. This is an encouraging advance in increasing our limited donor lung pool and may ultimately lead to improved rates of donor lung utilization. Human Organ Procurement and Exchange (HOPE) Program.
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 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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".