Passos Camila Ribeiro, Moreira Alexandre Altamir, Reis Ruy Freitas, Dos Santos Rodrigo Weber, Lobosco Marcelo, Rocha Bernardo Martins
Computational Engineering, Federal University of Juiz de Fora, Juiz de Fora 36036-900, Brazil.
Mechanical Engineering, Federal University of Juiz de Fora, Juiz de Fora 36036-900, Brazil.
BioTech (Basel). 2025 Mar 12;14(1):19. doi: 10.3390/biotech14010019.
The COVID-19 pandemic has underscored the importance of understanding the interplay between the cardiovascular and immune systems during viral infections. SARS-CoV-2 enters human cells via the ACE-2 enzyme, initiating a cascade of immune responses. This study presents a coupled mathematical model that integrates the cardiovascular system (CVS) and immune system (IS), capturing their complex interactions during infection. The CVS model, based on ordinary differential equations, describes heart dynamics and pulmonary and systemic circulation, while the IS model simulates immune responses to SARS-CoV-2, including immune cell interactions and cytokine production. A coupling strategy transfers information from the IS to the CVS at specific intervals, enabling the exploration of immune-driven cardiovascular effects. Numerical simulations examined how these interactions influence infection severity and recovery. The coupled model accurately replicated the evolution of cardiac function in survivors and non-survivors of COVID-19. Survivors exhibited a left ventricular ejection fraction (LVEF) reduction of up to 25% while remaining within normal limits, whereas non-survivors showed a severe 4-fold decline, indicative of myocardial dysfunction. Similarly, the right ventricular ejection fraction (RV EF) decreased by approximately 50% in survivors but underwent a drastic 5-fold reduction in non-survivors. These findings highlight the model's capacity to distinguish differential cardiac dysfunction across clinical outcomes and its potential to enhance our understanding of COVID-19 pathophysiology.
新冠疫情凸显了了解病毒感染期间心血管系统与免疫系统之间相互作用的重要性。严重急性呼吸综合征冠状病毒2(SARS-CoV-2)通过血管紧张素转换酶2(ACE-2)进入人体细胞,引发一系列免疫反应。本研究提出了一个耦合数学模型,该模型整合了心血管系统(CVS)和免疫系统(IS),捕捉了感染期间它们之间的复杂相互作用。基于常微分方程的心血管系统模型描述了心脏动力学以及肺循环和体循环,而免疫系统模型模拟了对SARS-CoV-2的免疫反应,包括免疫细胞相互作用和细胞因子产生。一种耦合策略以特定间隔将信息从免疫系统传递到心血管系统,从而能够探索免疫驱动的心血管效应。数值模拟研究了这些相互作用如何影响感染的严重程度和恢复情况。该耦合模型准确地复制了新冠病毒感染者幸存者和非幸存者心脏功能的演变。幸存者的左心室射血分数(LVEF)最多降低25%,但仍在正常范围内,而非幸存者则出现了严重的4倍下降,表明存在心肌功能障碍。同样,幸存者的右心室射血分数(RV EF)下降了约50%,而非幸存者则急剧下降了5倍。这些发现突出了该模型区分不同临床结果中心脏功能障碍的能力及其增强我们对新冠病毒病理生理学理解的潜力。