Novel effects of acute COVID‐19 on cardiac mechanical function: Two case studies
Bibliographic record
Abstract
The spread of the novel coronavirus 2019 (COVID-19) has caused a global pandemic. The disease has spread rapidly, and research shows that COVID-19 can induce long-lasting cardiac damage. COVID-19 can result in elevated cardiac biomarkers indicative of acute cardiac injury, and research utilizing echocardiography has shown that there is mechanical dysfunction in these patients as well, especially when observing the isovolumic, systolic, and diastolic portions of the cardiac cycle. The purpose of this study was to present two case studies on COVID-19 positive patients who had their cardiac mechanical function assessed every day during the acute period to show that cardiac function in these patients was altered, and the damage occurring can change from day-to-day. Participant 1 showed compromised cardiac function in the systolic time, diastolic time, isovolumic time, and the calculated heart performance index (HPI), and these impairments were sustained even 23 days post-symptom onset. Furthermore, Participant 1 showed prolonged systolic periods that lasted longer than the diastolic periods, indicative of elevated pulmonary artery pressure. Participant 2 showed decreases in systole and consequently, increases in HPI during the 3 days post-symptom onset, and these changes returned to normal after day 4. These results showed that daily observation of cardiac function can provide detailed information about the overall mechanism by which cardiac dysfunction is occurring and that COVID-19 can induce cardiac damage in unique patterns and thus can be studied on a case-by-case basis, day-to-day during infection. This could allow us to move toward more personalized cardiovascular medical treatment.
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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 | 0.001 | 0.107 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".