Revaccination of individuals with cardiac adverse events following COVID-19 vaccination: A Canadian Immunization Research Network study
Bibliographic record
Abstract
INTRODUCTION: Myocarditis and pericarditis are well-described rare adverse events following immunization (AEFI) associated with COVID-19 mRNA vaccines. Safety data on revaccination among people with previous cardiac AEFIs are lacking. This study assessed outcomes of COVID-19 revaccination among participants assessed for cardiac AEFIs. METHODS: The Special Immunization Clinic Network database, containing data from consented participants across twelve sites, was analyzed. Cases were classified using the Brighton Collaboration Case Definitions (BCCDs) for mutually exclusive diagnoses of myocarditis, myopericarditis or pericarditis. Subjects with cardiac symptoms not meeting the BCCD and with no alternative diagnosis were categorized as chest pain/other cardiac diagnosis. Revaccination recommendations were based on physician judgment, informed by national guidelines. Participants were followed up to 42 days after revaccination to capture AEFI recurrence. RESULTS: Between January 1, 2021 and February 23, 2023, 114 participants were enrolled, including 46 with myocarditis (40.4 %), 26 (22.8 %) with myopericarditis, 11 (9.6 %) with pericarditis, and 31 (27.1 %) with chest pain/other cardiac diagnosis. Twenty-seven of 71 participants (38.0 %) who required further COVID-19 vaccine doses were recommended for revaccination. Sixteen participants were revaccinated: two with myocarditis, two with myopericarditis, two with pericarditis and 10 with chest pain/other cardiac diagnosis. Four adults had recurrent symptoms of the AEFI: 2/10 with previous chest pain/other cardiac diagnosis, one participant with previous pericarditis and multiple comorbid conditions, and one participant with previous myopericarditis who required hospitalization. CONCLUSIONS: COVID-19 mRNA revaccination may be considered for individuals with chest pain not meeting criteria for myocarditis but caution is warranted in adults with prior confirmed myopericarditis post-COVID-19 mRNA vaccination.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".