School of Chemical, Materials, and Biomedical Engineering, University of Georgia, Athens, Georgia, United States of America.
Department of Epidemiology and Biostatistics, University of Georgia, Athens, Georgia, United States of America.
PLoS Comput Biol. 2020 Aug 17;16(8):e1008074. doi: 10.1371/journal.pcbi.1008074. eCollection 2020 Aug.
Congestive heart failure is characterized by suppressed cardiac output and arterial filling pressure, leading to renal retention of salt and water, contributing to further volume overload. Mathematical modeling provides a means to investigate the integrated function and dysfunction of heart and kidney in heart failure. This study updates our previously reported integrated model of cardiac and renal functions to account for the fluid exchange between the blood and interstitium across the capillary membrane, allowing the simulation of edema. A state of heart failure with reduced ejection fraction (HF-rEF) was then produced by altering cardiac parameters reflecting cardiac injury and cardiovascular disease, including heart contractility, myocyte hypertrophy, arterial stiffness, and systemic resistance. After matching baseline characteristics of the SOLVD clinical study, parameters governing rates of cardiac remodeling were calibrated to describe the progression of cardiac hemodynamic variables observed over one year in the placebo arm of the SOLVD clinical study. The model was then validated by reproducing improvements in cardiac function in the enalapril arm of SOLVD. The model was then applied to prospectively predict the response to the sodium-glucose co-transporter 2 (SGLT2) inhibitor dapagliflozin, which has been shown to reduce heart failure events in HF-rEF patients in the recent DAPAHF clinical trial by incompletely understood mechanisms. The simulations predict that dapagliflozin slows cardiac remodeling by reducing preload on the heart, and relieves congestion by clearing interstitial fluid without excessively reducing blood volume. This provides a quantitative mechanistic explanation for the observed benefits of SGLT2i in HF-rEF. The model also provides a tool for further investigation of heart failure drug therapies.
充血性心力衰竭的特征是心输出量和动脉充盈压降低，导致肾脏保留盐和水，进一步导致容量超负荷。数学模型为研究心力衰竭中心脏和肾脏的综合功能和功能障碍提供了一种手段。本研究更新了我们之前报告的心脏和肾脏功能综合模型，以考虑毛细血管膜两侧血液和间质之间的液体交换，从而模拟水肿。通过改变反映心脏损伤和心血管疾病的心脏参数，产生射血分数降低的心力衰竭（HF-rEF）状态，包括心脏收缩性、心肌肥大、动脉僵硬和全身阻力。在匹配 SOLVD 临床研究的基线特征后，对控制心脏重构速率的参数进行了校准，以描述 SOLVD 临床研究安慰剂组中观察到的心脏血流动力学变量在一年中的进展。然后通过复制 SOLVD 中依那普利组的心脏功能改善来验证该模型。然后将该模型应用于前瞻性预测钠-葡萄糖协同转运蛋白 2（SGLT2）抑制剂达格列净的反应，该抑制剂通过不完全了解的机制在最近的 DAPAHF 临床试验中降低了 HF-rEF 患者的心力衰竭事件。模拟预测达格列净通过减少心脏的前负荷来减缓心脏重构，并通过清除间质液而不会过度减少血容量来缓解充血。这为观察到 SGLT2i 在 HF-rEF 中的益处提供了一种定量的机制解释。该模型还为进一步研究心力衰竭药物治疗提供了一种工具。
