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Record W4367296578 · doi:10.1097/txd.0000000000001416

Organ and Tissue Donation Consent Model and Intent to Donate Registries: Recommendations From an International Consensus Forum

2023· article· en· W4367296578 on OpenAlexafffundabout
Phil Walton, Alicia Pérez‐Blanco, Stephen Beed, Alexandra K. Glazier, Daniela Ferreira Salomão Pontes, Jennifer Kingdon, Kim Jordison, Matthew J. Weiss

Bibliographic record

VenueTransplantation Direct · 2023
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsHôpital de l'Enfant-JésusTranslational Research in OncologyDalhousie University
FundersCanadian Blood Services
KeywordsMedicineOrgan donationDonationTissue DonationMEDLINEFamily medicineConsensus conferenceLawTransplantationSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Consent model and intent to donate registries are often the most public facing aspects of an organ and tissue donation and transplantation (OTDT) system. This article describes the output of an international consensus forum designed to give guidance to stakeholders considering reform of these aspects of their system. Methods: This Forum was initiated by Transplant Québec and cohosted by the Canadian Donation and Transplantation Program partnered with multiple national and international donation and transplantation organizations. This article describes the output of the consent and registries domain working group, which is 1 of 7 domains from this Forum. The domain working group members included administrative, clinical, and academic experts in deceased donation consent models in addition to 2 patient, family, and donor partners. Topic identification and recommendation consensus was completed over a series of virtual meetings from March to September 2021. Consensus was achieved by applying the nominal group technique informed by literature reviews performed by working group members. Results: Eleven recommendations were generated and divided into 3 topic groupings: consent model, intent to donate registry structure, and consent model change management. The recommendations emphasized the need to adapt all 3 elements to the legal, societal, and economic realities of the jurisdiction of the OTDT system. The recommendations stress the importance of consistency within the system to ensure that societal values such as autonomy and social cohesion are applied through all levels of the consent process. Conclusions: We did not recommend one consent model as universally superior to others, although considerations of factors that contribute to the successful deployment of consent models were discussed in detail. We also include recommendations on how to navigate changes in the consent model in a way that preserves an OTDT system's most valuable resource: public trust.

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)0.366
metaresearch head score (Gemma)0.379
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.366
Threshold uncertainty score0.782

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3660.379
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.006
Bibliometrics0.0100.007
Science and technology studies0.0090.007
Scholarly communication0.0130.018
Open science0.0100.013
Research integrity0.0220.022
Insufficient payload (model declined to judge)0.0060.003

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 head0.043
GPT teacher head0.332
Teacher spread0.289 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations16
Published2023
Admission routes3
Has abstractyes

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