ISHLT Consensus Statement on the Perioperative use of ECLS in Lung Transplantation: Part I: Preoperative Considerations
Bibliographic record
Abstract
The use of extracorporeal life support (ECLS) throughout the perioperative phase of lung transplantation requires nuanced planning and execution by an integrated team of multidisciplinary experts. To date, no multidisciplinary consensus document has examined the perioperative considerations of how to best manage these patients. To address this challenge, this perioperative utilization of ECLS in lung transplantation consensus statement was approved for development by the International Society for Heart and Lung Transplantation Standards and Guidelines Committee. International experts across multiple disciplines, including cardiothoracic surgery, anesthesiology, critical care, pediatric pulmonology, adult pulmonology, pharmacy, psychology, physical therapy, nursing, and perfusion, were selected based on expertise and divided into subgroups examining the preoperative, intraoperative, and postoperative periods. Following a comprehensive literature review, each subgroup developed recommendations to examine via a structured Delphi methodology. Following 2 rounds of Delphi consensus, a total of 50 recommendations regarding preoperative considerations for ECLS in lung transplantation met consensus criteria. These recommendations focus on the criteria for preoperative ECLS as well as select multidisciplinary team management considerations throughout the entire preoperative phase.
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 | 0.150 | 0.147 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".