首页> 外文期刊>Journal of Clinical Medicine >Clinical Usefulness of New R-R Interval Analysis Using the Wearable Heart Rate Sensor WHS-1 to Identify Obstructive Sleep Apnea: OSA and RRI Analysis Using a Wearable Heartbeat Sensor
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Clinical Usefulness of New R-R Interval Analysis Using the Wearable Heart Rate Sensor WHS-1 to Identify Obstructive Sleep Apnea: OSA and RRI Analysis Using a Wearable Heartbeat Sensor

机译:使用可穿戴心率传感器WHS-1识别阻塞性睡眠呼吸暂停的新R-R间隔分析的临床有用性:OSA和RRI使用可穿戴心跳传感器的分析

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Obstructive sleep apnea (OSA) is highly associated with cardiovascular diseases, but most patients remain undiagnosed. Cyclic variation of heart rate (CVHR) occurs during the night, and R-R interval (RRI) analysis using a Holter electrocardiogram has been reported to be useful in screening for OSA. We investigated the usefulness of RRI analysis to identify OSA using the wearable heart rate sensor WHS-1 and newly developed algorithm. WHS-1 and polysomnography simultaneously applied to 30 cases of OSA. By using the RRI averages calculated for each time series, tachycardia with CVHR was identified. The ratio of integrated RRIs determined by integrated RRIs during CVHR and over all sleep time were calculated by our newly developed method. The patient was diagnosed as OSA according to the predetermined criteria. It correlated with the apnea hypopnea index and 3% oxygen desaturation index. In the multivariate analysis, it was extracted as a factor defining the apnea hypopnea index ( r = 0.663, p = 0.003) and 3% oxygen saturation index ( r = 0.637, p = 0.008). Twenty-five patients could be identified as OSA. We developed the RRI analysis using the wearable heart rate sensor WHS-1 and a new algorithm, which may become an expeditious and cost-effective screening tool for identifying OSA.
机译:阻塞性睡眠呼吸暂停(OSA)与心血管疾病高度相关,但大多数患者仍未结束。心率(CVHR)的循环变异在夜间发生,并且据报道,使用HOLTER心电图的R-R间隔(RRI)分析可用于筛选OSA。我们调查了RRI分析使用可穿戴心率传感器WHS-1和新开发的算法识别OSA的有用性。 WHS-1和多面体摄影同时应用于30例OSA。通过使用每次序列计算的RRI平均值,鉴定了具有CVHR的心动过速。通过新开发的方法计算通过CVHR和所有睡眠时间内集成RRI确定的集成RRI的比率。根据预定标准,患者被诊断为OSA。它与呼吸暂停缺氧指数和3%的氧去饱和指数相关。在多变量分析中,将其提取为定义呼吸暂停次酮指数(r = 0.663,p = 0.003)和3%氧饱和度指数(r = 0.637,p = 0.008)。二十五名患者可以被识别为OSA。我们使用可穿戴心率传感器WHS-1和新算法开发了RRI分析,这可能成为识别OSA的迅速且经济高效的筛选工具。

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