International review of blood donation screening for anti‐HBc and occult hepatitis B virus infection
Bibliographic record
Abstract
BACKGROUND: Hepatitis B core antibody (anti-HBc) screening has been implemented in many blood establishments to help prevent transmission of hepatitis B virus (HBV), including from donors with occult HBV infection (OBI). We review HBV screening algorithms across blood establishments globally and their potential effectiveness in reducing transmission risk. MATERIALS AND METHODS: A questionnaire on HBV screening and follow-up strategies was distributed to members of the International Society of Blood Transfusion working party on transfusion-transmitted infectious diseases. Screening data from 2022 were assimilated and analyzed. RESULTS: A total of 30 unique responses were received from 25 countries. Sixteen respondents screened all donations for anti-HBc, with 14 also screening all donations for HBV DNA. Anti-HBc prevalence was 0.42% in all blood donors and 1.19% in new donors in low-endemic countries; however, only 44% of respondents performed additional anti-HBc testing to exclude false reactivity. 0.68% of anti-HBc positive, HBsAg-negative donors had detectable HBV DNA. Ten respondents did universal HBV DNA screening without anti-HBc, whereas four respondents did not screen for either. Deferral strategies for anti-HBc positive donors were highly variable. One transfusion-transmission from an anti-HBc negative donor was reported. DISCUSSION: Anti-HBc screening identifies donors with OBI but also results in the unnecessary deferral of a significant number of donors with resolved HBV infection and donors with false-reactive anti-HBc results. Whilst confirmation of anti-HBc results could be improved to reduce donor deferral, transmission risks associated with anti-HBc negative OBI donors must be considered. In high-endemic areas, highly sensitive HBV DNA testing is required to identify infectious donors.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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; a candidate call from one teacher head, 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".