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Record W4378214580 · doi:10.3389/ti.2023.11012

Solid Organ Donation and Transplantation in the United Kingdom: Good Governance is Key to Success

2023· review· en· W4378214580 on OpenAlexaff
Charlotte Johnston-Webber, Jasmine Mah, Apostolos Prionas, Simon Streit, George Wharton, John Forsythe, Elías Mossialos, Vassilios Papalois

Bibliographic record

VenueTransplant International · 2023
Typereview
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsDalhousie University
FundersAlexander S. Onassis Public Benefit Foundation
KeywordsOrgan donationMedicineDonationTransplantationCorporate governanceOrgan transplantationPublic relationsSurgeryPolitical scienceBusinessLawFinance

Abstract

fetched live from OpenAlex

The United Kingdom (UK) supports a highly successful organ donation and transplantation program. While the UK originally had one of the lowest organ donation rates in Europe, sustained reforms have resulted in steady improvement. Of note, the UK nearly doubled its rate of deceased donations between 2008 and 2018. In this report, we present a case study of the UK organ donation and transplantation program as an example of a complete system with sound and inclusive governing structures that are strongly integrated with critical programs focused on training and research. This study was based on an initial targeted review of the literature led by a UK expert that included guidelines, national reports, and academic papers. Feedback solicited from other European experts was incorporated into our findings via an iterative process. Overall, the study highlights the stepwise evolution of the UK program that ultimately became successful largely due to ongoing collaborative efforts carried out at all levels. Centralized coordination of all aspects of the program remains a key driver of improved rates of organ donation and transplantation. The designation and empowerment of expert clinical leadership have helped to maintain focus and promote ongoing quality improvement.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.924
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.083
GPT teacher head0.393
Teacher spread0.310 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations22
Published2023
Admission routes1
Has abstractyes

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