Immunogenicity of bivalent versus monovalent mRNA booster vaccination among adult paramedics in Canada who had received three prior mRNA wild-type doses
Bibliographic record
Abstract
Introduction. Comparative immunogenicity from different mRNA booster vaccines (directed at WT, BA.1 or BA.4/5 antigens) remains unclear. Methods. We included blood samples from adult paramedics who received three mRNA WT-directed vaccines plus a fourth dose of the following: (1) WT monovalent, (2) Moderna BA.1-WT bivalent or (3) Pfizer BA.4/5 WT bivalent vaccine. The primary outcome was angiotensin-converting enzyme 2 (ACE2) inhibition to BA.4/5 antigen. We used optimal pair matching (using age, sex-at-birth, preceding SARS-CoV-2 infection and fourth vaccine-to-blood collection interval) to create balanced groups to individually compare each vaccine type to each other vaccine (overall, within subgroups defined by SARS-CoV-2 infection and after combining BA.1 and BA.4/5 cases). We compared outcomes with the Wilcoxon matched-pairs signed rank test. Results. Overall, 158 paramedics (mean age 45 years) were included. ACE2 inhibition was higher for BA.1 compared to WT ( P =0.002); however, no difference was detected between BA.4/5 vs. WT or BA.1 vs. BA.4/5. Among cases with preceding SARS-CoV-2, there were no detected between-group differences. Among cases without preceding SARS-CoV-2, the only detected difference was BA.1>WT ( P =0.003). BA.1 and BA.4/5 cases combined had higher ACE2 inhibition than WT ( P =0.003). Conclusion. Omicron-directed vaccines appear to improve Omicron-specific immunogenicity; however, this appears limited to SARS-CoV-2-naive individuals.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".