Implications of heart rate variability measured using wearable electrocardiogram devices in diagnosing Parkinson's disease and its association with neuroimaging biomarkers: a case-control study

利用可穿戴心电图设备测量的心率变异性在帕金森病诊断中的应用及其与神经影像学生物标志物的关系:一项病例对照研究

阅读:2

Abstract

INTRODUCTION: Heart rate variability (HRV) reflects cardiac autonomic regulation, and reduced HRV is associated with Parkinson's disease (PD). However, studies regarding the implications of HRV measures for the clinical manifestations of PD have shown inconclusive results. We examined the relationship between HRV measures obtained via long-term monitoring using a wearable electrocardiogram (ECG) device and the diagnosis and clinical characteristics of PD. METHODS: Seventeen controls and 20 patients with PD were prospectively enrolled. The HRV measures were recorded using a wearable ECG device for up to 72 h. Time- and frequency-domain measures were derived from the HRV analysis, and their association with PD diagnosis and clinical features was investigated. We investigated their association with neuroimaging biomarkers using magnetic resonance imaging to explore the underlying neural correlates. RESULTS: The diagnosis of PD was associated with several HRV measures, including a decreased standard deviation of N-N intervals, standard deviation of all heart rates, and low-frequency (LF) power. Among these HRV measures, only LF power was associated with clinical features of PD. LF power was positively correlated with the tremor sub-score (r = 0.500; p = 0.035) and negatively associated with the left (r = -0.598; p = 0.024) and right (r = -0.693; p = 0.006) cerebellar hemispheres in patients with PD. CONCLUSION: Low-frequency power may be used as a biomarker for tremor-associated pathophysiology of PD. Moreover, a wearable ECG device with its capability for long-term monitoring might be a promising tool for diagnosing PD.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。