Perfect Storm: COVID-19 Associated Cardiac Injury and Implications for Neurological Disorders
Bibliographic record
Abstract
Coronavirus disease 2019 (COVID-19) can lead to considerable lung damage and even death. Less is known about the effects of COVID-19 on the cardiovascular system. In their recent JAMA Cardiology article, Shi and colleagues reported an association between cardiac injury and higher risk of in-hospital mortality in patients with COVID-19. Approximately 20% (82 patients) of the study cohort presented with a cardiac injury. The investigators identified cardiac injury as an independent risk factor of mortality during hospitalization (52% with cardiac injury vs. 5% without cardiac injury, p < 0.001). Consequently, their findings are highly relevant for patients with pre-existing cardiovascular and cerebrovascular diseases. Among those are patients with neurological disorders. There is a considerable prevalence of myocardial injury in patients with acute neurological illness, which appears to adversely affect prognosis. Individuals with an underlying neurological disorder are particularly vulnerable to increased cardio-cerebrovascular disease risk due to physical limitations and the pathophysiology of their condition. Thus, we would like to specifically highlight the attention of health care professionals treating patients with pervasive neurological disorders to their potentially elevated risk of poorer COVID-19 related outcomes.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".