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Cardiovascular Coupling-Based Classification of Ischemic and Dilated Cardiomyopathy Patients

机译:基于心血管耦合的缺血性和扩张型心肌病患者分类

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Cardiovascular diseases are one of the most common causes of death in elderly patients. The etiology of cardiomyopathies is difficult to discern clinically. The objective of this study was to classify cardiomyopathy patients using coupling analysis, through their cardiovascular behavior and the baroreflex response. A total of thirty-eight cardiomyopathy patients (CMP) classified as ischemic (ICM, 25 patients) and dilated (DCM, 13 patients) were analyzed. Thirty elderly control subjects (CON) were used as reference. Their electrocardiographic (ECG) and blood pressure (BP) signals were studied. To characterize the cardiovascular activity, the following temporal series were extracted: beat-to-beat intervals (from the ECG signal), and end- systolic and diastolic blood pressure amplitudes (from the BP signal). Non-linear characterization techniques like high resolution joint symbolic dynamics, segmented Poincaré plot analysis, normalized shorttime partial directed coherence, and dual sequence method were used to characterize these times series. The best indices were used to build support vector machine models for classification. The optimal model for ICM versus DCM patients achieved 84.2% accuracy, 76.9% sensitivity, and 88% specificity. When CMP patients and CON subjects were compared, the best model achieved 95.5% accuracy, 97.3% sensitivity, and 93.3% specificity. These results suggest a disfunction in the baroreflex mechanism in cardiomyopathies patients.
机译:心血管疾病是老年患者最常见的死亡原因之一。心肌病的病因在临床上很难辨别。这项研究的目的是通过耦合分析,通过心血管行为和压力反射反应对心肌病患者进行分类。总共分析了38例分为缺血性(ICM,25例)和扩张型(DCM,13例)的心肌病患者(CMP)。以30名老年对照受试者(CON)为参考。研究了他们的心电图(ECG)和血压(BP)信号。为了表征心血管活动,提取了以下时间序列:心跳间隔(从ECG信号)以及收缩末期和舒张压的血压幅度(从BP信号)。高分辨率表征符号动力学,分段庞加莱图分析,归一化的短时局部有向相干和双序列方法等非线性表征技术被用来表征这些时间序列。最佳索引用于构建支持向量机模型进行分类。针对ICM与DCM患者的最佳模型实现了84.2%的准确性,76.9%的敏感性和88%的特异性。当比较CMP患者和CON受试者时,最好的模型达到了95.5%的准确性,97.3%的敏感性和93.3%的特异性。这些结果表明,心肌病患者的压力反射机制失调。

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