Management of non-response to Hepatitis B re-vaccination
Bibliographic record
Abstract
BACKGROUND: Bloodborne viruses, including Hepatitis B (HBV), are a known occupational hazard for healthcare workers (HCWs), particularly those involved in exposure-prone procedures. Whilst standard vaccines can provide immunity, 5-10% of people remain non-responders (anti-HBs titre <10IU/L) despite repeated vaccinations. Fendrix® (HBV recombinant DNA vaccine) has been shown to be highly effective in renal patients and those with human immunodeficiency virus, implying it may also have benefits for healthy non-responders. AIMS: Our analysis set out to identify and compare response rates to re-vaccination (with Fendrix® or HBvaxPro40®) in HCWs with non-response to standard vaccination procedures. METHODS: Between 1 March 2010 and 30 April 2024, either Fendrix® or HBvaxPro40® was offered to HCWs with inadequate response to two courses of Engerix B® standard vaccination. Antibody tests were performed 6 weeks post-final vaccine dose. Serological results from this period were retrospectively statistically analysed to compare differential vaccine responses. RESULTS: Eighty-five HCWs were identified as non-responders and offered further vaccination (42 received Fendrix® and 43 received HBvaxPro40®). Fendrix® resulted in a seroconversion rate of 95% (40/42) compared to 72% (31/43) with HBvaxPro40®; a significantly higher number responded more strongly to Fendrix® (74% versus 23%). CONCLUSIONS: Our results demonstrate the rationale for offering additional vaccination with Fendrix® to HCWs when standard vaccination and repeated administration has not elicited an adequate immune response. Multi-centre evaluation of this vaccination strategy for non-responder HCWs should be considered to generate evidence for the most acceptable and efficacious approach.
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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 | 0.000 |
| 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) | 0.002 | 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".