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Record W4408804803 · doi:10.1111/vox.70021

Removal of deferrals for variant Creutzfeldt–Jakob disease risk: Impact on new and previously deferred donors

2025· article· en· W4408804803 on OpenAlexaffabout
Mindy Goldman, David McKee, Shane Smith, Sheila F. O’Brien

Bibliographic record

VenueVox Sanguinis · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPrion Diseases and Protein Misfolding
Canadian institutionsCanadian Blood ServicesUniversity of Ottawa
Fundersnot available
KeywordsMedicineDeferralDonationSurgeryBlood donorQuarter (Canadian coin)Family medicineDemographyLawFinance

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: Concern over variant Creutzfeldt-Jakob disease (vCJD) led to the deferral of donors who had resided in the United Kingdom since January 1980. This deferral was implemented in 1999 and subsequently modified to include other countries. Some deferrals were removed in February 2022; deferrals for the United Kingdom, Ireland and France were removed on 22 November 2023. In this study, we describe efforts made to encourage donation from newly eligible people and the resulting donation gain. MATERIALS AND METHODS: Actions targeted individual donors deferred after 1 January 2012. Marketing included website, social media and general advertising. Staff asked first-time donors if the criteria change had motivated their donation. Deferred and returning donor data were determined from our donor database. RESULTS: In the 12 months post-implementation, 12.8% of first-time donors surveyed were newly eligible (n = 8667) and 7.8% of vCJD risk deferred donors returned (n = 5159). Eighty-five percent of deferrals occurred pre-2017; the return rate was 6.5% in this group. The highest return rate (24%) occurred in donors deferred after 2020. CONCLUSION: Removal of the vCJD deferrals had a major positive impact. The greatest gain was in new donors who had previously self-deferred. Despite intensive efforts, only one-quarter of recently deferred donors returned.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.709
Threshold uncertainty score0.630

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.012
GPT teacher head0.306
Teacher spread0.294 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations0
Published2025
Admission routes2
Has abstractyes

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