Hepatitis B virus (HBV) DNA screening of blood donations in minipools with the COBAS AmpliScreen HBV test
Bibliographic record
Abstract
BACKGROUND: The risk of hepatitis B virus (HBV) transmission by blood transfusion (estimated at 1 in 63,000-1 in 205,000 units in the United States) exceeds that of hepatitis C virus (HCV) or human immunodeficiency virus (HIV). Reduction of window-period HBV transmissions through detection of HBV DNA-positive units by minipool nucleic acid testing (MP NAT) would be expected to decrease this risk. STUDY DESIGN AND METHODS: A large multicenter study of the COBAS AmpliScreen HBV test (Roche Molecular Systems) was conducted on minipools of 24 blood donation specimens. The yield of HBV DNA-positive, hepatitis B surface antigen (HBsAg)-negative window-period donations was determined relative to current and newly licensed HBsAg assays. Donors with selected HBV DNA, HBsAg, and anti-hepatitis B core antigen (HBc) results were further evaluated. RESULTS: The detection rate of window-period units was 1 in 352,451 (95% confidence interval, 1 in 2,941,176-1 in 97,561). Assay specificity was high (99.9964%). HBV DNA was detected in 84 percent of HBsAg-positive, anti-HBc-positive donations by MP NAT and in 94 percent when individual-donation (ID) NAT was added. HBV DNA was detected in 0.03 percent of HBsAg-negative, anti-HBc-positive donations by MP NAT and in 0.41 percent when ID NAT was added. CONCLUSIONS: Implementation of HBV MP NAT will provide an increment in safety relative to HBV serologic screening, similar to that for HCV and in excess of that for HIV. Our data indicate that the implementation of HBV MP NAT would likely interdict 39 HBV window-period units and prevent 56 cases of transfusion-transmitted HBV infection annually. The current data indicate that HBV MP NAT should not lead to discontinuation of anti-HBc testing but that discontinuation of HBsAg testing with retention of anti-HBc testing may be possible.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".