Monitoring syphilis serology in blood donors: Is there utility as a surrogate marker of early transfusion transmissible infection behavioral risk?
Bibliographic record
Abstract
BACKGROUND: In Canada the time deferral for gay, bisexual, and other men who have sex with men (gbMSM) was progressively shortened (lifetime, 5 years, 1 year, 3 months). Here we describe trends in syphilis rates (a potential sexual risk marker) and risk behaviors from blood donors in the past 12 years. STUDY DESIGN AND METHODS: Syphilis positivity in 10,288,322 whole blood donations (January 1, 2010-September 10, 2022) and gbMSM deferral time periods, donation status, age, and sex were analyzed with logistic regression. Overall, 26.9% syphilis positive and 42.2% controls (matched 1:4) participated in risk factor interviews analyzed by logistic regression. RESULTS: Syphilis rates were higher in first-time donors (OR 27.0, 95% CI 22.1-33.0), in males (OR 2.3, 1.9-2.8) and with the 3-month deferral (OR 3.4, 2.6-4.3) during which the increase was greater for first-time males (p < .001) but similar for male and female repeat donors (p > .05). Among first-time donors, histories of intravenous drug use (OR 11.7, 2.0-69.5), male-to-male sex 7.8 (2.0-30.2) and birth in a high prevalence country (OR 7.6, 4.4-13.0) predicted syphilis positivity; among repeat donors, history of male-to-male sex (OR 33.5, CI 3.5-317.0). All but 1 gbMSM syphilis-positive donors were noncompliant with the gbMSM deferral. About a quarter of first-time interviewed case donors had history of syphilis; 44% were born in a high-prevalence country. CONCLUSION: Rising syphilis rates in donors correlates with the general population epidemic. Recent infection rates rose similarly in males and females. GbMSM history may contribute to donor syphilis rates but shortening time deferrals appears unrelated.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".