Scarsoglio Stefania, Ridolfi Luca
Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Torino, Italy.
Department of Environmental, Land and Infrastructure Engineering, Politecnico di Torino, Torino, Italy.
Front Neurosci. 2021 May 17;15:600574. doi: 10.3389/fnins.2021.600574. eCollection 2021.
Heart rate variability (HRV), defined as the variability between consecutive heartbeats, is a surrogate measure of cardiac vagal tone. It is widely accepted that a decreased HRV is associated to several risk factors and cardiovascular diseases. However, a possible association between HRV and altered cerebral hemodynamics is still debated, suffering from HRV short-term measures and the paucity of high-resolution deep cerebral data. We propose a computational approach to evaluate the deep cerebral and central hemodynamics subject to physiological alterations of HRV in an ideal young healthy patient at rest. The cardiovascular-cerebral model is composed by electrical components able to reproduce the response of the different cardiovascular regions and their features. The model was validated over more than thirty studies and recently exploited to understand the hemodynamic mechanisms between cardiac arrythmia and cognitive deficit. Three configurations (baseline, increased HRV, and decreased HRV) are built based on the standard deviation (SDNN) of RR beats. For each configuration, 5,000 RR beats are simulated to investigate the occurrence of extreme values, alteration of the regular hemodynamics pattern, and variation of mean perfusion/pressure levels. In the cerebral circulation, our results show that HRV has overall a stronger impact on pressure than flow rate mean values but similarly alters pressure and flow rate in terms of extreme events. By comparing reduced and increased HRV, this latter induces a higher probability of altered mean and extreme values, and is therefore more detrimental at distal cerebral level. On the contrary, at central level a decreased HRV induces a higher cardiac effort without improving the mechano-contractile performance, thus overall reducing the heart efficiency. Present results suggest that: (i) the increase of HRV does not seem to be sufficient to trigger a better cerebral hemodynamic response; (ii) by accounting for both central and cerebral circulations, the optimal HRV configuration is found at baseline. Given the relation inversely linking HRV and HR, the presence of this optimal condition can contribute to explain why the mean HR of the general population settles around the baseline value (70 bpm).
心率变异性（HRV）被定义为连续心跳之间的变异性，是心脏迷走神经张力的替代指标。人们普遍认为，HRV降低与多种风险因素和心血管疾病有关。然而，HRV与脑血流动力学改变之间的可能关联仍存在争议，这是由于HRV短期测量方法以及高分辨率深部脑数据的匮乏所致。我们提出一种计算方法，用于评估理想状态下静息的年轻健康患者在HRV发生生理改变时的深部脑血流动力学和中心血流动力学。心血管-脑模型由能够再现不同心血管区域反应及其特征的电气元件组成。该模型在三十多项研究中得到验证，最近被用于理解心律失常与认知缺陷之间的血流动力学机制。基于RR间期的标准差（SDNN）构建了三种配置（基线、HRV增加和HRV降低）。对于每种配置，模拟5000个RR间期，以研究极值的出现、正常血流动力学模式的改变以及平均灌注/压力水平的变化。在脑循环中，我们的结果表明，总体而言，HRV对压力的影响比对平均流速的影响更强，但在极端事件方面，对压力和流速的改变相似。通过比较HRV降低和增加的情况，后者导致平均和极值改变的可能性更高，因此在脑远端水平更具危害性。相反，在中心水平，HRV降低会导致更高的心脏负荷，而不会改善机械收缩性能，从而总体上降低心脏效率。目前的结果表明：（i）HRV的增加似乎不足以引发更好的脑血流动力学反应；（ii）综合考虑中心和脑循环，最佳HRV配置出现在基线状态。鉴于HRV与心率呈反比关系，这种最佳状态的存在有助于解释为什么普通人群的平均心率稳定在基线值（70次/分钟）左右。
