Platiša Mirjana M, Radovanović Nikola N, Pernice Riccardo, Barà Chiara, Pavlović Siniša U, Faes Luca
Laboratory for Biosignals, Institute of Biophysics, Faculty of Medicine, University of Belgrade, Višegradska 26-2, 11000 Belgrade, Serbia.
Pacemaker Center, University Clinical Center of Serbia, University of Belgrade, 11000 Belgrade, Serbia.
Entropy (Basel). 2023 Jul 17;25(7):1072. doi: 10.3390/e25071072.
The properties of cardio-respiratory coupling (CRC) are affected by various pathological conditions related to the cardiovascular and/or respiratory systems. In heart failure, one of the most common cardiac pathological conditions, the degree of CRC changes primarily depend on the type of heart-rhythm alterations. In this work, we investigated CRC in heart-failure patients, applying measures from information theory, i.e., Granger Causality (), Transfer Entropy () and Cross Entropy (), to quantify the directed coupling and causality between cardiac () and respiratory () time series. Patients were divided into three groups depending on their heart rhythm (sinus rhythm and presence of low/high number of ventricular extrasystoles) and were studied also after cardiac resynchronization therapy (CRT), distinguishing responders and non-responders to the therapy. The information-theoretic analysis of bidirectional cardio-respiratory interactions in HF patients revealed the strong effect of nonlinear components in the (high number of ventricular extrasystoles) and in the time series (respiratory sinus arrhythmia) as well as in their causal interactions. We showed that as a linear model measure is not sensitive to both nonlinear components and only model free measures as and may quantify them. CRT responders mainly exhibit unchanged asymmetry in the values, with statistically significant dominance of the information flow from to over the opposite flow from to , before and after CRT. In non-responders this asymmetry was statistically significant only after CRT. Our results indicate that the success of CRT is related to corresponding information transfer between the cardiac and respiratory signal quantified at baseline measurements, which could contribute to a better selection of patients for this type of therapy.
心肺耦合（CRC）的特性受与心血管和/或呼吸系统相关的各种病理状况影响。在心力衰竭（最常见的心脏病理状况之一）中，CRC变化程度主要取决于心律改变的类型。在这项研究中，我们对心力衰竭患者的CRC进行了研究，应用信息论中的方法，即格兰杰因果关系（）、转移熵（）和交叉熵（），来量化心脏（）和呼吸（）时间序列之间的定向耦合和因果关系。根据患者的心律（窦性心律以及室性早搏数量的高低）将其分为三组，并在心脏再同步治疗（CRT）后进行研究，区分治疗的反应者和无反应者。对心力衰竭患者双向心肺相互作用的信息论分析揭示了室性早搏数量多的时间序列和呼吸性窦性心律不齐的时间序列中的非线性成分及其因果相互作用的强烈影响。我们表明，作为线性模型度量对这两种非线性成分均不敏感，只有像转移熵和交叉熵这样的无模型度量可以对它们进行量化。CRT反应者在转移熵值方面主要表现出不对称性不变，在CRT前后，从心脏到呼吸的信息流相对于从呼吸到心脏的相反信息流在统计学上具有显著优势。在无反应者中，这种不对称性仅在CRT后具有统计学意义。我们的结果表明，CRT的成功与基线测量时量化的心脏和呼吸信号之间相应的信息传递有关，这可能有助于更好地选择适合这种治疗类型的患者。
