Cardiovascular Health and Disease in the Context of COVID-19
Bibliographic record
Abstract
First documented in China in early December 2019, the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread rapidly and continues to test the strength of healthcare systems and public health programs all over the world. Underlying cardiovascular disease has been recognized as a risk factor for coronavirus disease 2019 (COVID-19)-related morbidity and mortality since the early days of the pandemic. In addition, evidence demonstrates cardiac and endothelial damage in somewhere between one-third and three-quarters of individuals with COVID-19, regardless of symptom severity. This damage is thought to be mediated by direct viral infection, immunopathology and hypoxemia with the additional possibility of exacerbation via medication-induced cardiotoxicity. Clinically, the cardiovascular consequences of COVID-19 may present as myocarditis with or without arrhythmia, endothelial dysfunction and thrombosis, acute coronary syndromes and heart failure. Presentation can vary widely and may or may not be typical of the condition in an individual without COVID-19. There is evidence to support the prognostic utility of cardiac biomarkers (e.g., cardiac troponin) and imaging studies (e.g., echocardiography, cardiac magnetic resonance imaging) in the context of COVID-19 and building evidence suggests that cardiovascular screening may be warranted even among those with asymptomatic or mild infection and those without traditional cardiovascular risk factors. In addition, evidence suggests the potential for long-term cardiovascular consequences for those who recover from COVID-19 with implications for the field of cardiology long into the future. Even among those without COVID-19, disruption of infrastructure and changes in human behavior as a result of the pandemic also have an upstream role in cardiovascular outcomes, which have already been documented in multiple locations. This review summarizes what is currently known regarding the pathogenic mechanisms of COVID-19-related cardiovascular injury and describes clinical cardiovascular presentations, prognostic indicators, recommendations for screening and treatment, and long-term cardiovascular consequences of infection. Ultimately, medical personnel must be vigilant in their attention to possible cardiovascular symptoms, take appropriate steps for clinical diagnosis and be prepared for long-term ramifications of myocardial injury sustained as a result of COVID-19.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".