Recondicionamento pulmonar ex vivo: uma nova era para o transplante pulmonar
Bibliographic record
Abstract
Lung transplantation has come to be viewed as the best treatment option for various end-stage lung diseases. The low number of viable donors continues to be a major obstacle to increasing the number of lung transplants, resulting in high mortality among patients on the waiting list. Unlike transplantation of other solid organs, lung transplantation is primarily limited not by the absolute number of donors but by the viability of the donor lungs, which can be damaged by brain death and by treatments given in the ICU. There are various proposals of ways to increase the number of lung donors: intensification of donation campaigns, use of non-heart-beating donors, living lobar lung transplantation, and adoption of more flexible criteria for donors. However, the proposal that has attracted the most attention from lung transplant groups is ex vivo lung perfusion, especially due to the prospect of reconditioning previously discarded lungs. This system consists of perfusion and ventilation of the isolated heart-lung block using a modified cardiopulmonary bypass circuit. Various authors have been studying this technique due to the satisfactory results obtained and the prospect of an increase in the number of organs suitable for transplantation. Researchers in Sweden, Canada, Austria, England, Spain, and Brazil have extensive experience with the method and have introduced modifications to it. The objective of this article was to review the development of, state of the art in, and future prospects for the ex vivo model of lung perfusion and reconditioning.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".