MétaCan
Menu
Back to cohort
Record W4367307049 · doi:10.1097/txd.0000000000001446

Research and Innovation in Organ Donation: Recommendations From an International Consensus Forum

2023· article· en· W4367307049 on OpenAlexafffund
Manuel Escoto, Fadi Issa, Florence Cayouette, Henrietta K. Consolo, Prosanto Chaudhury, Sonny Dhanani, Wenshi Jiang, Gabriel C. Oniscu, Nicholas A. Murphy, Karen Rockell, Matthew J. Weiss, Mélanie Dieudé

Bibliographic record

VenueTransplantation Direct · 2023
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsUniversité de MontréalHéma-QuébecWestern UniversityCentre Hospitalier de l’Université de MontréalChildren's Hospital of Eastern OntarioUniversity of OttawaMcGill University Health CentreTranslational Research in Oncology
FundersMedical Research CouncilCanadian Blood Services
KeywordsMedicineOrgan donationDonationLegislaturePublic relationsResearch ethicsTransplantationMedical educationPolitical scienceSurgery

Abstract

fetched live from OpenAlex

This report provides recommendations from the Research and Innovation domain as part of the International Donation and Transplantation Legislative and Policy Forum (hereafter the Forum) to provide expert guidance on the structure of an ideal organ and tissue donation and transplantation system. The recommendations focus on deceased donation research and are intended for clinicians, investigators, decision-makers, and patient, family, and donor (PFD) partners involved in the field. Methods: We identified topics impacting donation research through consensus using nominal group technique. Members performed narrative reviews and synthesized current knowledge on each topic, which included academic articles, policy documents, and gray literature. Using the nominal group technique, committee members discussed significant findings, which provided evidence for our recommendations. The Forum's scientific committee then vetted recommendations. Results: We developed 16 recommendations in 3 key areas to provide stakeholders guidance in developing a robust deceased donor research framework. These include PFD and public involvement in research; donor, surrogate, and recipient consent within a research ethics framework; and data management. We highlight the importance of PFD and public partner involvement in research, we define the minimum ethical requirements for the protection of donors and recipients of both target and nontarget organ recipients, and we recommend the creation of a centrally administered donor research oversight committee, a single specialist institutional review board, and a research oversight body to facilitate coordination and ethical oversight of organ donor intervention research. Conclusions: Our recommendations provide a roadmap for developing and implementing an ethical deceased donation research framework that continually builds public trust. Although these recommendations can be applied to jurisdictions developing or reforming their organ and tissue donation and transplantation system, stakeholders are encouraged to collaborate and respond to their specific jurisdictional needs related to organ and tissue shortages.

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 imitation

Not 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.

metaresearch head score (Codex)0.443
metaresearch head score (Gemma)0.482
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.443
Threshold uncertainty score0.686

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4430.482
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0050.012
Bibliometrics0.0150.011
Science and technology studies0.0100.015
Scholarly communication0.0270.041
Open science0.0140.027
Research integrity0.0490.045
Insufficient payload (model declined to judge)0.0110.007

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 head0.080
GPT teacher head0.396
Teacher spread0.316 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueTransplantation DirectSame topicOrgan Donation and TransplantationFrench-language works237,207