The NHLBI lung transplant consortium 2025 steering committee report: Strategies to maximize the use of the consortium for advancing lung transplantation
Bibliographic record
Abstract
The Lung Transplant Consortium (LTC), sponsored by the National Heart, Lung, and Blood Institute (NHLBI) is a 20-center collaboration among lung transplant programs in North America conducting both smaller multicenter projects and one consortium-wide prospective observational cohort study called the Prospective Multicenter Research on Donor and Recipient Management Strategies to Improve Lung Transplant Outcomes (PROMISE) Lung Study-for more information about the LTC, visit their website: https://lungtransplantconsortium.org/. The LTC conducted a meeting in April 2025 to strategize how to maximize the benefits of the PROMISE study to advance the field of lung transplant. This paper summarizes the key themes that emerged from the meeting: leveraging PROMISE data elements, including biomarkers, imaging, and PROs; clinical syndrome and consensus definitions; variation in management and management strategies; and future interventional trials leveraging the PROMISE consortium. The PROMISE study will serve as the platform for establishing best practices in lung transplant, inform the validity of newly identified syndromes, and support analysis of patient-reported outcomes, image data, and biosamples. The PROMISE study and LTC create a critically needed research platform and multicenter collaborative structure that may be adapted to conduct future multicenter clinical trials that will advance lung transplant medicine.
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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 | 0.209 | 0.178 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.016 | 0.006 |
| Open science | 0.006 | 0.011 |
| Research integrity | 0.027 | 0.019 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".