Residual risk of transfusion‐transmitted hepatitis B virus (<scp>TT‐HBV</scp>) infection by <scp>NAT</scp>‐screened blood components: A review of observed versus modeled infectivity from donors with window period and occult <scp>HBV</scp> infections
Bibliographic record
Abstract
BACKGROUND: The residual transfusion-transmitted hepatitis B virus (TT-HBV) risk with different testing strategies depends on the sensitivity of screening assays, the prevalence of hepatitis B surface antigen (HBsAg) compared to HBV-DNA in window period (WP) and occult HBV infections (OBIs), and infectivity of blood in these infection stages. We compared modeled WP and OBI transmission risk in a multiregional individual donation nucleic acid amplification technology (ID-NAT) screening study with observed TT-HBV infection rates in several lookback studies. STUDY DESIGN AND METHODS: ), a key factor in the applied risk models, was assumed to be 100-fold higher in OBI than in WP blood. The relative proportion of WP and OBI TT-risk was estimated for different screening scenarios and expressed as a percentage of the ID-NAT yield rate to allow for comparison with observed TT-rates in lookback studies. RESULTS: Despite sevenfold to eightfold higher HBV ID-NAT yield rates in OBI than WP in South-East Asia and Europe, our models predicted that 40 (26-55)% of total residual TT-HBV risk was due to OBI, comparable to 37% observed in a Japanese hemovigilance study. Modeled TT-OBI risk was approximately 10-fold higher than observed rates of 2%-8% in five lookback studies but comparable to one other study (36%). CONCLUSION: Although the observed TT-OBI rate was generally lower than the modeled risk, the relative risk of WP versus OBI transmission was not incompatible with the observational infectivity data. This supports the validity of our assumptions in the infectivity-based models for estimating worst-case residual risk with different testing scenarios.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".