Modeling the cardiac response to hemodynamic changes associated with COVID-19: a computational study

Area of Science:

• Cardiovascular Medicine
• Computational Biology
• Infectious Diseases

Background:

• COVID-19 infection is increasingly linked to cardiovascular complications.
• These complications include myocardial injury, acute coronary syndrome, myocarditis, arrhythmia, and heart failure.
• Understanding the cardiovascular impact of COVID-19 is crucial for patient management.

Purpose of the Study:

• To investigate the interplay between local cardiac changes, global cardiovascular variables, and overall cardiac function in COVID-19 patients.
• To develop and utilize a computational model to simulate cardiovascular and pulmonary interactions.
• To assess cardiac function parameters in virtual subjects with varying COVID-19 severity.

Main Methods:

• Employed a lumped parameters computational model of the cardiovascular system.
• Utilized a three-dimensional multiphysics model of cardiac electromechanics.
• Simulated systemic and pulmonary circulations, cardiac valves, and chambers using physical process equations.

Main Results:

• The computational model successfully simulated cardiovascular dynamics.
• Assessed key cardiac function parameters through numerical simulations.
• Revealed interactions between cardiac and pulmonary functions in simulated COVID-19 scenarios.

Conclusions:

• A novel computational model can effectively reveal cardiac and pulmonary function interactions.
• The model aids in understanding cardiovascular impacts of COVID-19 in diverse patient profiles.
• This approach offers insights for prospective treatment strategies in COVID-19 patients with cardiac involvement.