The high prevalence of occult hepatitis B infections among the partners of chronically infected HBV blood donors emphasizes the potential residual risk to blood safety
Bibliographic record
Abstract
A small percentage of couples who regularly donated blood in China tested positive for HBsAg. Although it is well known that blood donors can acquire hepatitis B virus (HBV) infection from a chronically infected sexual partner, the prevalence of occult hepatitis B infections (OBIs) among blood donations from partners of HBV-infected chronically infected spouses and the risk to blood safety remain poorly understood. Among 212 763 blood donors, 54 pairs of couples (108 donations) were enrolled because one partner tested positive for HBsAg. Several molecular and serological examinations were conducted. The origin of HBV transmission between sexual partners was investigated further. Also evaluated was the potential risk of HBV infection with OBIs. We identified 10 (10/54, 18.6%) sexual partners of chronically infected HBV donors who were positive for HBV DNA, including five samples (9.3%) with OBIs, of which 3 (3/54, 5.6%, 1 in 70 921 donations) passed the routine blood screening tests. Seven of the 10 HBV-DNA-positive couples contracted the virus possibly through sexual or close contact. Among infected couples, immune escape mutations were observed. A high prevalence of OBIs was found among the partners of chronically infected HBV blood donors, posing a potential threat to blood safety.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.004 | 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".