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Record W4376598454 · doi:10.1016/j.vaccine.2023.05.010

The persistence of seroprotective levels of antibodies after vaccination with PreHevbrio, a 3-antigen hepatitis B vaccine

2023· article· en· W4376598454 on OpenAlexaffabout
Timo Vesikari, Joanne M. Langley, Johanna N. Spaans, И. А. Петров, Vlad Popovic, Bebi Yassin-Rajkumar, David E. Anderson, Francisco Díaz‐Mitoma

Bibliographic record

VenueVaccine · 2023
Typearticle
Languageen
FieldMedicine
TopicHepatitis B Virus Studies
Canadian institutionsNova Scotia Health AuthorityDalhousie UniversityHealth Canada
Fundersnot available
KeywordsMedicineHepatitis B virusVaccinationHepatitis BPersistence (discontinuity)Hepatitis B vaccineAntibodyAntigenImmunologyAntibody titerVirologyTiterInternal medicineVirusHBsAg

Abstract

fetched live from OpenAlex

Prevention of hepatitis B virus (HBV) infection by vaccination can potentially eliminate HBV-related diseases. PreHevbrio™/PreHevbri® is a 3-antigen (S, preS1, preS2) HBV vaccine (3A-HBV) recently licensed for adults in the US, EU and Canada. This study evaluated antibody persistence in a subset of fully vaccinated and seroprotected (anti-HBs ≥ 10 mIU/mL) Finnish participants from the phase 3 trial (PROTECT) of 3A-HBV versus single-antigen HBV vaccine (1A-HBV). 465/528 eligible subjects were enrolled (3A-HBV: 244; 1A-HBV: 221). Baseline characteristics were balanced. After 2.5 years, more 3A-HBV subjects remained seroprotected (88.1 % [95 %CI: 84.1,92.2]) versus 1A-HBV (72.4 % [95 %CI: 66.6,78.3)], p < 0.0001) and had higher mean anti-HBs [1382.9 mIU/mL (95 %CI: 1013.8,1751.9) versus 252.6 mIU/mL (95 %CI: 127.5,377.6), p < 0.0001]. In multiple variable logistic regression analysis including age, vaccine, initial vaccine response, sex and BMI, only higher post dose 3 (Day 196) antibody titers significantly reduced the odds of losing seroprotection.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.026
GPT teacher head0.272
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2023
Admission routes2
Has abstractyes

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