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Record W4229083761 · doi:10.3390/vaccines10050722

Risk of Myocarditis and Pericarditis among Young Adults following mRNA COVID-19 Vaccinations

2022· article· en· W4229083761 on OpenAlexaff
Abdallah Alami, Daniel Krewski, Donald R. Mattison, Kumanan Wilson, Christopher A. Gravel, Paul J. Villeneuve, Paul J. Farrell, James A. G. Crispo, Santiago Perez‐Lloret

Bibliographic record

VenueVaccines · 2022
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Immunology Research
Canadian institutionsNOSM UniversityUniversity of British ColumbiaMcGill UniversityOttawa HospitalBruyèreUniversity of OttawaCarleton University
Fundersnot available
KeywordsPericarditisCoronavirus disease 2019 (COVID-19)VaccinationMyocarditisMedicine2019-20 coronavirus outbreakVirologySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)ImmunologyCardiologyInternal medicineOutbreakDisease

Abstract

fetched live from OpenAlex

There have been reports of cases of myocarditis and pericarditis as rare complications following mRNA COVID-19 vaccinations among young adults. While most reported cases are mild, this potential vaccine safety signal should be closely monitored. Using data from the CDC and the Vaccine Adverse Event Reporting System (VAERS), we calculated the combined reporting rate of myocarditis and pericarditis stratified by age group, sex, vaccine dose, and manufacturer, and compared these rates to the crude background incidence rates. Compared to the general population prior to the administration of the first COVID-19 vaccines in December 2020, we identified a higher-than-expected reporting rate of myocarditis and pericarditis following mRNA vaccination; the risk was higher after a second vaccine dose, higher in males than in females, and decreased with age. The highest risk was seen in males 12-17 years of age with approximately 6 cases per 100,000 second doses. Our findings suggest an increased risk of myocarditis and pericarditis in young males following a second dose of an mRNA COVID-19 vaccine. Since these findings are based on safety signals derived from passive surveillance data, confirmatory epidemiological studies should be undertaken.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.004
Threshold uncertainty score0.603

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.294
Teacher spread0.281 · 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 teacher head, 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

Citations21
Published2022
Admission routes1
Has abstractyes

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