Imaging Acute and Chronic Cardiac Complications of COVID-19 and after COVID-19 Vaccination
Bibliographic record
Abstract
COVID-19 is associated with acute and longer-term cardiovascular manifestations including myocardial injury, myopericarditis, stress-induced cardiomyopathy, myocardial infarction, and thromboembolic disease. Although the morbidity and mortality related to acute COVID-19 have decreased substantially, there is growing concern about the longer-term cardiovascular effects of the disease and postacute sequelae. Myocarditis has also been reported after messenger ribonucleic acid (mRNA)–based COVID-19 vaccination, with the highest risk among adolescent boys and young adult men. Noninvasive imaging including cardiac MRI has a key role in identifying the presence of cardiovascular disease, evaluating for potential mechanisms of injury, stratifying risk of future adverse cardiovascular events, and potentially guiding treatment in patients with suspected cardiovascular injury after COVID-19 and vaccination. Patterns of injury identified at cardiac MRI after COVID-19 include myocarditis and pericarditis, myocardial ischemia, and infarction. Myocardial edema and late gadolinium enhancement have been described months after the initial infection in a minority of patients with persistent cardiac symptoms after COVID-19. In patients with myocarditis after receiving a COVID-19 vaccination, the most common pattern of late gadolinium enhancement is subepicardial at the basal inferolateral wall, and patients tend to have milder imaging abnormalities compared with those from other causes of myocarditis. This article describes the role of multimodality cardiac imaging and imaging findings in patients with acute and longer-term cardiovascular manifestations of COVID-19 and in patients with myocarditis after receiving an mRNA-based COVID-19 vaccination. ©RSNA, 2023 Online supplemental material is available for this article. Quiz questions for this article are available through the Online Learning Center.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".