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Maximal-radius multiscale entropy of cardiovascular variability: A promising biomarker of pathological mood states in bipolar disorders

机译:心血管变异的最大半径多尺度熵:双相情感障碍病理性情绪状态的有前途的生物标志物

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Complexity measures from Multiscale Entropy (MSE) analysis of cardiovascular variability may provide potential biomarkers of pathological mental states such as major depression. To this extent, in this study we investigate whether complexity of Heart Rate Variability (HRV) is also affected in mental disorders such as bipolar disorders (BD). As part of the European project PSYCHE, eight BD patients experiencing multiple pathological mood states among depression, hypomania, and euthymia (i.e., good affective balance) underwent long-term night recordings through a comfortable sensing t-shirt with integrated fabric electrodes and sensors. Standard radius, i.e., 20% of the HRV standard deviation, and a maximal-radius choice for the sample entropy estimation were compared along with a further multiscale Renyi Entropy analysis. We found that, despite the inter-subject variability, the maximal-radius MSE analysis is able to discern the considered pathological mental states of BD. As the current clinical practice in diagnosing BD is only based on verbal interviews and scores from specific questionnaires, these findings provide evidence on the possibility of using heartbeat complexity as the basis of novel clinical biomarkers of mental disorders.
机译:来自多尺度熵(MSE)的心血管变异性分析的复杂性指标可能为病理性精神状态(例如重度抑郁症)提供潜在的生物标志物。在这个程度上,在这项研究中,我们调查了心率变异性(HRV)的复杂性在精神疾病(如躁郁症)中是否也受到影响。作为欧洲PSYCHE项目的一部分,八名BD患者经历了抑郁,轻躁狂和耳聋(即良好的情感平衡)之间的多种病理性情绪状态,并通过舒适的感应T恤(带有集成的织物电极和传感器)进行了长期夜间录音。比较了标准半径(即HRV标准偏差的20%)和样本熵估计的最大半径选择,以及进一步的多尺度Renyi熵分析。我们发现,尽管受试者之间存在差异,但最大半径MSE分析仍能够辨别出所考虑的BD的病理性心理状态。由于目前诊断BD的临床实践仅基于口头访谈和特定问卷的得分,因此这些发现为将心跳复杂性用作精神疾病新型临床生物标志物的可能性提供了证据。

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