Detection and characterization of hepatitis B virus of anti‐hepatitis B core antigen–reactive blood donors in Quebec with an in‐house nucleic acid testing assay
Bibliographic record
Abstract
BACKGROUND: Hepatitis B virus (HBV) infection can be detected in blood donations by many serologic markers. Since the introduction of routine anti-hepatitis B core antigen (HBc) donor screening at Héma-Québec in April 2003, a large number of donors have been deferred on the basis of reactive anti-HBc test results. The objective of this study was to evaluate the correlation between the anti-HBc-reactive donations and the detection of HBV DNA with an in-house nucleic acid testing (NAT) assay. STUDY DESIGN AND METHODS: The in-house HBV NAT assay is a conventional polymerase chain reaction amplifying part of the viral S gene. From October 2004 to November 2005, a total of 1169 anti-HBc-reactive donations were tested with this in-house assay. The results were correlated with hepatitis B surface antigen (HBsAg) and anti-HBs markers. HBV DNA-positive samples were further investigated by DNA sequencing. RESULTS: All HBsAg-positive samples were detected by the NAT assay. Overall, 38 (3.25%) of anti-HBc-positive samples were found to be positive for the presence of HBV DNA. Of these 38, a total of 12 donations with a low level of HBV DNA were HBsAg-negative. The sequencing results clearly showed various genotypes and subtypes within a same genotype. CONCLUSION: The 3.25 percent HBV DNA positivity rate among the anti-HBc-reactive donations and more particularly the low level of HBV DNA observed in occult donations underline the importance of the use of a sensitive assay to detect HBV DNA in conjunction with other markers. The HBV genetic diversity found in our donor population reflects the province demographics, particularly in the Montreal area where most of the positive donors were from.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".