Assessing the Elevation of Cardiac Biomarkers and the Severity of COVID-19 Infection: A Meta-analysis
Bibliographic record
Abstract
- Purpose: Since December 2019, coronavirus disease 2019 infection has become a global pandemic. The cases of Coronavirus Disease 2019 (COVID-19)-related acute cardiac injury with unknown pathophysiologic mechanism has become increasingly prevalent. However, it is not yet understood how the extent of cardiac injury differs with the intensity of viral infection. In the current study, we aimed to assess the association between elevated cardiac biomarkers and the severity of COVID-19 infection. METHODS: A systematic literature search was performed across PubMed and Embase databases from December 1, 2019 to July 10, 2020, to identify studies that reported cardiac biomarkers of troponin (TnI) and creatine kinase-myocardial band (CK-MB) in patients with COVID-19. These studies compared non-severe patients with severe patients, or survivors with non-survivors or medical patients with critically ill patients. The data were extracted for TnI, CK-MB, N-terminal-brain natriuretic peptide (NT-BNP), D-dimer, and lactate dehydrogenase (LDH), C-reactive protein (CRP), and interleukin 6 (IL-6). Wherever possible, the data were pooled for meta-analysis (Review Manager, RevMan. version 5.3) with standard or weighted mean or median difference and corresponding 95% confidence intervals (95% CI). RESULTS: A total of 25 studies involving 5,626 patients were included in the present analysis. More severe COVID-19 infection was found to be associated with higher mean values of TnI (-0.54 [-0.72, -0.36]) (ng/mL), CK-MB (-1.55 [-2.23, -0.88]) (ng/mL) and (-4.75 [-13.31, 3.82]) (units/L), NT-BNP (-815.7 [-1073.97, -557.42]) (pg/mL), D-dimer (-1.4 [-2.04, -0.77]) (mcg/mL), and LDH (-176.59 [-224.11, -129.06]) (units/L), as well as CRP (-64.03 [-68.88, -59.19]) (mg/L) and IL-6 (-22.59 [-29.39, -15.79]) (pg/mL). CONCLUSIONS: There is significant association between elevated cardiac biomarkers and the severity of COVID-19, which underlines the increased risk of acute cardiac injury with more severe viral infection. This highlights the need to understand the cardiac history among the COVID-19 patients during initial assessment and for monitoring.
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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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.053 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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 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".