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The risks and benefits of accepting men who have had sex with men as blood donors

2003· article· en· W2030624365 on OpenAlexaff
Marc Germain, Robert S. Remis, Gilles Delage

Bibliographic record

VenueTransfusion · 2003
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBlood donation and transfusion practices
Canadian institutionsUniversity of TorontoHéma-Québec
Fundersnot available
KeywordsMen who have sex with menDeferralDemographyMedicineHuman immunodeficiency virus (HIV)ImmunologySyphilis

Abstract

fetched live from OpenAlex

BACKGROUND: It has been suggested that men who have had sex with men (MSM) should become eligible to donate blood if they recently abstained from male-to-male sex. STUDY DESIGN AND METHODS: The impact of a 12-month deferral policy for MSM on the risk of introducing contaminated units in the blood supply and the benefit of obtaining additional donations were estimated. Considered were the prevalence of HIV among MSM, the window period of infection, the rate of laboratory testing errors, and the occurrence of other system failures. This was compared with the risk and benefit that currently results from accepting female donors who have had sex with MSM. RESULTS: The revised policy for MSM would potentially result in one HIV-contaminated unit for every 136,000 additional donations (95% CI, 1 in 69,000 to 1 in 268,000), for an overall increase in HIV risk estimated at 8 percent. The number of donations would increase by 1.3 percent (95% CI, 0.9%-1.7%). The risk-benefit ratio of currently accepting female partners of MSM is approximately five times lower. CONCLUSION: The risk increment of accepting 12-month abstinent MSM would be very small but not zero. From a risk-benefit perspective, the current deferral policy for MSM is more efficient compared to an analogous hypothetical criterion for female partners of MSM.

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)0.004
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.024
GPT teacher head0.246
Teacher spread0.222 · 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 designObservational
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

Citations61
Published2003
Admission routes1
Has abstractyes

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