MétaCan
Menu
Back to cohort
Record W4404580636 · doi:10.1111/vox.13773

Has the switch to sexual risk behaviour screening impacted deferrals for pre‐ and post‐exposure prophylaxis therapy for human immunodeficiency virus?

2024· article· en· W4404580636 on OpenAlexaffabout
Mindy Goldman, Samra Uzicanin, Sheila F. O’Brien

Bibliographic record

VenueVox Sanguinis · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBlood donation and transfusion practices
Canadian institutionsCanadian Blood ServicesUniversity of Ottawa
Fundersnot available
KeywordsMedicineDeferralHuman immunodeficiency virus (HIV)Pre-exposure prophylaxisEpidemiologySurgeryDemographyInternal medicineImmunologyMen who have sex with men

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: Canadian Blood Services defers donors during and for 4 months after oral pre-exposure or post-exposure prophylaxis (PrEP/PEP) for human immunodeficiency virus (HIV) because of concerns about altered viral kinetics. We assessed the impact of the switch from a time-based deferral for men who have sex with men (MSM) to sexual risk behaviour criteria on PrEP/PEP deferrals. MATERIALS AND METHODS: Data on PrEP/PEP deferral codes were extracted from our National Epidemiology Database for the 22 months before (Period 1) and after (Period 2) the criteria change. RESULTS: PEP deferrals remained stable (2.3 vs. 1.7 per 100,000 donations in Periods 1 and 2, p = 0.2892), about 45% and 33%, respectively, of these donors who reported a recent needle stick injury. PrEP deferrals increased from 5.9 to 12.4 per 100,000 (p = 0.0001); approximately 30% of donors in both periods had other HIV risk factor deferrals. Donors deferred for PrEP use alone were more likely to be male, first-time users and younger than other donors. CONCLUSION: The switch to sexual risk behaviour led to a small increase in deferrals for PrEP. We may not be measuring the full impact of deferral criteria because potential donors may self-defer and PrEP use is increasing.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.781
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.001
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 head0.043
GPT teacher head0.311
Teacher spread0.269 · 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 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

Citations1
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueVox SanguinisSame topicBlood donation and transfusion practicesFrench-language works237,207