<scp>HBV</scp> deferrals and <scp>NAT</scp> window period: Assessing the impact of 3‐month versus 4‐month testing delays
Bibliographic record
Abstract
BACKGROUND: Héma-Québec (Québec, Canada) currently defers prospective blood donors for 3, 6, or 12 months depending on their self-reported risk factors for hepatitis B virus (HBV) infection. However, this policy may be needlessly complex and overly cautious, thereby potentially causing confusion among donors and deferring those with an acceptable safety profile. Based on published window period estimates, a uniform deferral period of 3 or 4 months may be considered. To inform our policy update, we estimated the incremental risk of adopting an HBV deferral period of 4 months versus 3 months. STUDY DESIGN AND METHODS: This probit analysis was an adaptation of the Weusten model. The analysis considered the characteristics of the current nucleic acid test (NAT)-HBV assay (i.e., Procleix Ultrio plus assay in minipools of 16) and HBV viral dynamics. The incremental risk of banking an HBV-contaminated whole blood donation was evaluated through a Monte-Carlo simulation in which 10,000 infected donors were simulated; corresponding to 833 years of observation. RESULTS: . Of the 10,000 simulated infected donors, 32 (and 104 using an eclipse phase [EP] of 8 days) would test negative by NAT between 3 and 4 months post-HBV exposure, corresponding to one HBV contamination every 7.8 (or 2.4 using the 8-day EP) million donations. DISCUSSION: Adopting an HBV deferral of 3 months poses a negligible incremental risk compared with 4 months and is acceptable given the resulting gain in newly eligible donors.
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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 | 0.014 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".