The interplay between COVID-19 and heart disease : unravelling a complex connection

Abstract

The intersection of coronavirus (COVID-19) and heart disease has emerged as a critical nexus in the landscape of global health. Individuals with heart disease face elevated risks when infected with Severe Acute Respiratory-Syndrome Coronavirus-type-2 (SARS-CoV-2) leading to COVID-19. The virus can directly affect the heart, resulting in myocarditis, arrhythmias, and heart failure, even in individuals without prior medical cardiac history. Therefore, tools identifying patients with cardiac infestation and predicting disease severity are of utmost importance. This study's unbiased stratification of clinical and immunological parameters of 134 SARS-CoV-2 positive patients revealed clusters of course-severity within the established WHO ordinal severity-scale leading to its summary (SWOSS) into three categories, A-C. PE and SWOSS-C were significantly associated with reduced survival of COVID-19 patients. The previously introduced CD8/Treg/monocyte-ratio which hints at a dysfunctional antiviral immunity associated with poor prognosis could be verified in this larger study population. However, the number of circulating CD14 + HLA-DR+ monocytes represented the most significant predictor for myocardial damage indicated by PE. We used all available data for an unbiased examination of associations and predictions by machine learning algorithms: Predictive markers for PE can be obtained in clinic and may serve as prognostic features. Among numerous parameters, C-reactive protein (CRP) was the most important in determining the presence of PE and SWOSS-category. Prediction of survival was most relevantly influenced by SWOSS-category underlining the benefit of this condensed classification for clinical practice. All AI-revealed prognostic features serve as promising starting-point to gain further understanding of the interplay between COVID-19 and heart disease.