COVID-19 and myocarditis: a review of literature
Bibliographic record
Abstract
Myocarditis has been discovered to be a significant complication of coronavirus disease 2019 (COVID-19), a condition caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. COVID-19 myocarditis seems to have distinct inflammatory characteristics, which make it unique to other viral etiologies. The incidence of COVID-19 myocarditis is still not clear as a wide range of figures have been quoted in the literature; however, it seems that the risk of developing myocarditis increases with more severe infection. Furthermore, the administration of the mRNA COVID-19 vaccine has been associated with the development of myocarditis, particularly after the second dose. COVID-19 myocarditis has a wide variety of presentations, ranging from dyspnea and chest pain to acute heart failure and possibly death. It is important to catch any cases of myocarditis, particularly those presenting with fulminant myocarditis which can be characterized by signs of heart failure and arrythmias. Initial work up for suspected myocarditis should include serial troponins and electrocardiograms. If myocardial damage is detected in these tests, further screening should be carried out. Cardiac magnetic resonance imagining and endomyocardial biopsy are the most useful tests for myocarditis. Treatment for COVID-19 myocarditis is still controversial; however, the use of intravenous immunoglobulins and corticosteroids in combination may be effective, particularly in cases of fulminant myocarditis. Overall, the incidence of COVID-19 myocarditis requires further research, while the use of intravenous immunoglobulins and corticosteroids in conjunction requires large randomized controlled trials to determine their efficacy.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".