Pediatric Myocarditis and Pericarditis Complication after mRNA-based COVID-19 Vaccination
Bibliographic record
Abstract
Oyster and co-authors (2022) have authored an article called Myocarditis cases reported after mRNA-based COVID-19 vaccination in the United States from December 2020 to August 2021, which studies and investigates the resulting number of cases of Myocarditis concerning the COVID-19 vaccination for pediatric patients older than 12 years of age but include individuals less than 30 years of age. From analyzing COVID 19 vaccination, there is more attribute towards the benefits associated with health matters as outlined by Bozkurt and co-authors (2021). However, from the research, the vaccination holds potential risks that would harm the population involved (Halushka & Vander Heide, 2021). The article investigates the different reports of Myocarditis and pericarditis rates after mRNA-based vaccination in the United States and globally. With the detailed information, the article has reviewed additional existing knowledge to support the study’s objective. Public health Ontario 2022 also provides an overview of the event of Myocarditis and Pericarditis following mRNA COVID 19 vaccines. Data from other countries also reported Cases of Myocarditis/Pericarditis following immunization with mRNA vaccine in Ontario, Canada, and internationally. Reported cases have occurred more frequently in males under 30 years, following the second dose, usually within one week of vaccination, and have mild with quick recovery. Although they also mention that the benefit of vaccination continues to outweigh the risk of COVID-19 illness, the authority still recommends vaccination for all eligible individuals, including children and youth. Also, per the American college of cardiology, vaccine-associated Myocarditis is a rare but possible side effect after m-RNA based COVID-19 vaccine. The clinical course of this Myocarditis is generally mild, with most symptoms resolving quickly.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".