MétaCan
Menu
Back to cohort
Record W3183806681 · doi:10.1016/j.healun.2021.07.005

Consensus document for the selection of lung transplant candidates: An update from the International Society for Heart and Lung Transplantation

2021· article· en· W3183806681 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Heart and Lung Transplantation · 2021
Typearticle
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsHospital for Sick ChildrenSickKids FoundationUniversity of Toronto
FundersNational Heart, Lung, and Blood InstituteHealth Resources and Services AdministrationLung Foundation NetherlandsBoomer Esiason FoundationZonMwSavara PharmaceuticalsEuropean Respiratory SocietyBristol-Myers SquibbAstellas PharmaUnited Therapeutics CorporationCystic Fibrosis FoundationGalectoVertex PharmaceuticalsNational Institutes of HealthU.S. Department of Health and Human Services
KeywordsLungSelection (genetic algorithm)Lung transplantationTransplantationMedicineIntensive care medicineInternal medicineComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Tens of thousands of patients with advanced lung diseases may be eligible to be considered as potential candidates for lung transplant around the world each year. The timing of referral, evaluation, determination of candidacy, and listing of candidates continues to pose challenges and even ethical dilemmas. To address these challenges, the International Society for Heart and Lung Transplantation appointed an international group of members to review the literature, to consider recent advances in the management of advanced lung diseases, and to update prior consensus documents on the selection of lung transplant candidates. The purpose of this updated consensus document is to assist providers throughout the world who are caring for patients with pulmonary disease to identify potential candidates for lung transplant, to optimize the timing of the referral of these patients to lung transplant centers, and to provide transplant centers with a framework for evaluating and selecting candidates. In addition to addressing general considerations and providing disease specific recommendations for referral and listing, this updated consensus document includes an ethical framework, a recognition of the variability in acceptance of risk between transplant centers, and establishes a system to account for how a combination of risk factors may be taken into consideration in candidate selection for lung transplantation.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.478
Threshold uncertainty score0.376

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.327
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it