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Record W4298008708 · doi:10.1136/bmjopen-2022-067515

Protocol for a qualitative pilot study to explore ethical issues and stakeholder trust in the use of normothermic regional perfusion in organ donation in Canada

2022· article· en· W4298008708 on OpenAlexafffundabout
Nicholas B. Murphy, Lorelei Lingard, Laurie Blackstock, Mary Ott, Marat Slessarev, John Basmaji, Mayur Brahmania, Andrew Healey, Sam D. Shemie, Anton Skaro, Lindsay Wilson, Charles Weijer

Bibliographic record

VenueBMJ Open · 2022
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsCanadian Blood ServicesMcGill University Health CentreTrillium Therapeutics (Canada)Montreal Children's HospitalMcMaster UniversityLondon Health Sciences CentreWestern University
FundersCanadian Donation and Transplantation Research Program
KeywordsMedicineOrgan donationStakeholderDonationBioethicsMEDLINETransplantationEngineering ethicsPublic relationsSurgeryPolitical scienceLaw

Abstract

fetched live from OpenAlex

Introduction The process of controlled organ donation after circulatory determination of death (cDCDD) results in ischaemic injury to organs and leads to poorer outcomes in organ recipients. Although not yet used in Canada, normothermic regional perfusion (NRP) is a perfusion technology used postmortem with cDCDD donors to selectively restore perfusion of oxygenated blood to target organs in situ, reversing ischaemic injury and improving organ viability and post-transplant outcomes. However, NRP poses significant ethical challenges. To preserve trust in deceased donation, these ethical challenges must be addressed to the satisfaction of Canadian stakeholders before NRP’s implementation. This study will identify ethical issues pertaining to NRP and explore perspectives of NRP among key stakeholders. By developing an explanatory framework delineating how stakeholder perceptions of NRP’s ethical implications impact trust in Canada’s donation and transplantation systems, this study will inform the development of responsible policy on NRP’s use in Canada. Methods and analysis This study includes two workstreams. Workstream 1 is a scoping review of medical and bioethical literature to identify ethical issues stemming from NRP. We will apply a common search string across Medline, PubMed (other than Medline) and Embase to identify relevant articles. We will identify grey literature through Google searches, websites of organ donation organisations and consultation with our research network. No date limits will be applied. All peer-reviewed publications, commentaries, editorials or documents that engage with ethical issues in NRP (or conceptual and empirical issues as they relate to these ethical issues) will be included. News articles, conference abstracts and publications not in English will be excluded. Workstream 2 consists of interviews with healthcare providers, institutional stakeholders, organ recipients and deceased donors’ family members (n=24–36), as well as focus groups with healthcare providers involved in deceased donation and transplantation (n = 20–32). Constructivist grounded theory methodology will guide data collection and analysis in workstream 2. Ethics and dissemination This study was approved by Western University’s research ethics committee (Western REM; ID: 120001). All participants will be asked to provide written informed consent to participate. Findings will be shared with Canadian organ donation and transplantation organisations, presented at national conferences and published in medical journals.

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)0.051
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.920
Threshold uncertainty score0.272

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0510.047
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0040.004
Science and technology studies0.0140.007
Scholarly communication0.0060.004
Open science0.0040.005
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0660.007

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 head0.572
GPT teacher head0.508
Teacher spread0.064 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreProtocol

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

Citations4
Published2022
Admission routes3
Has abstractyes

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