A multiprovincial retrospective analysis of the incidence of myocarditis or pericarditis after mRNA vaccination compared to the incidence after SARS-CoV-2 infection
Bibliographic record
Abstract
Objective: To compare myocarditis/pericarditis risk after COVID-19 mRNA vaccination versus SARS-CoV-2 infection, and to assess if myocarditis/pericarditis risk varies by vaccine dosing interval. Methods: In this retrospective cohort study, we used linked databases in Quebec, Ontario, and British Columbia between January 26, 2020, and September 9, 2021. We included individuals aged 12 or above who received an mRNA vaccine as the second dose or were SARS-CoV-2-positive by RT-PCR. The outcome was hospitalization/emergency department visit for myocarditis/pericarditis within 21 days of exposure. We calculated age- and sex-stratified incidence ratios (IRs) of myocarditis/pericarditis following mRNA vaccination versus SARS-CoV-2 infection. We also calculated myocarditis/pericarditis incidence by vaccine type, homologous/heterologous schedule, and dosing interval. We pooled province-specific estimates using meta-analysis. Results: Following 18,860,817 mRNA vaccinations and 860,335 SARS-CoV-2 infections, we observed 686 and 160 myocarditis/pericarditis cases, respectively. Myocarditis/pericarditis incidence was lower after vaccination than infection (IR [BNT162b2/SARS-CoV-2], 0.14; 95%CI, 0.07-0.29; IR [mRNA-1273/SARS-CoV-2], 0.28; 95%CI, 0.20-0.39). Within the vaccinated cohort, myocarditis/pericarditis incidence was lower with longer dosing intervals; IR (56 or more days/15-30 days) was 0.28 (95%CI, 0.19-0.41) for BNT162b2 and 0.26 (95%CI, 0.18-0.38) for mRNA-1273. Conclusion: Myocarditis/pericarditis risk was lower after mRNA vaccination than SARS-CoV-2 infection, and with longer intervals between primary vaccine doses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| 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) | 0.000 | 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 teacher head, 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".