Abstract
Frontiers requested research on how a systems approach can explore the mechanisms of cardiovascular complications in Covid-19. The focus of this paper will thus be on these detailed mechanisms. It will elucidate the integrated pathogenic pathways based on an extensive review of literature. Many severe Covid-19 cases and deaths occur in patients with chronic cardiovascular comorbidities. To help understand all the mechanisms of this interaction, Covid-19 complications were integrated into a pre-existing systems-based coronary heart disease (CHD) model. Such a complete model could not be found in literature. A fully integrative view could be valuable in identifying new pharmaceutical interventions, help understand how health factors influence Covid-19 severity and give a fully integrated explanation for the Covid-19 death spiral phenomenon seen in some patients. Covid-19 data showed that CHD hallmarks namely, Hypercoagulability, Hypercholesterolemia, Hyperglycemia/Hyperinsulinemia, Inflammation and Hypertension have an important effect on disease severity. The pathogenic pathways that Covid-19 activate in CHD were integrated into the CHD model. This fully integrated model presents a visual explanation of the mechanism of interaction between CHD and Covid-19 complications. This includes a detailed integrated explanation of the death spiral as a result of interactions between Inflammation, endothelial cell injury, Hypercoagulability and hypoxia. Additionally, the model presents the aggravation of this death spiral through the other CHD hallmarks namely, Hyperglycemia/Hyperinsulinemia, Hypercholesterolemia, and/or Hypertension. The resulting model further suggests systematically how the pathogenesis of nine health factors (stress, exercise, smoking, etc.) and seven pharmaceutical interventions (statins, salicylates, thrombin inhibitors, etc.) may either aggravate or suppress Covid-19 severity. A strong association between CHD and Covid-19 for all the investigated health factors and pharmaceutical interventions, except for β-blockers, was found. It is further discussed how the proposed model can be extended in future to do computational analysis to help assess the risk of Covid-19 in cardiovascular disease. With insight gained from this study, recommendations are made for future research in potential new pharmacotherapeutics. These recommendations could also be beneficial for cardiovascular disease, which killed five times more people in the past year than Covid-19.