Obstructive sleep apnea syndrome (OSAS) is a common sleep disorder. It has been reported that approximately 40% of patients with moderate or severe OSAS die within the first eight years of disease. In hospitals, OSAS ...Obstructive sleep apnea syndrome (OSAS) is a common sleep disorder. It has been reported that approximately 40% of patients with moderate or severe OSAS die within the first eight years of disease. In hospitals, OSAS is inspected using polysomnography, which uses a number of sensors. Because of the cumbersome nature of this polysomnography, an initial OSAS screening is usually conducted. In recent years, OSAS screening techniques using Holter electrocardiogram (ECG) have been reported. However, the techniques so far reported cannot perform an OSAS severity assessment. The present study presents a new method to distinguish the obstructive sleep apnea (OSA) and non-OSA epochs at one-second intervals based on the Apnea Hypopnea Index assessment, defined as the duration of continuous apnea. In the proposed method, the time-frequency components of the heart rate variability and three ECG-derived respiration signals calculated by the complex Morlet wavelet transformation are adopted as features. A support vector machine is employed for classification. The proposed method is evaluated using three eight-hour ECG recordings containing OSA episodes from three subjects. As a result, the sensitivity and specificity of classification are found to reach approximately 90%, a level suitable for OSAS screening in clinical settings.展开更多
目的探讨肥胖合并重度阻塞性睡眠呼吸暂停低通气综合征(obstructive sleep apnea hypopnea syndrome,OSAHS)患者的心率变异性(heart rate variability,HRV)特征。方法回顾性分析2018年4月至2022年5月在西安交通大学第二附属医院行多导睡...目的探讨肥胖合并重度阻塞性睡眠呼吸暂停低通气综合征(obstructive sleep apnea hypopnea syndrome,OSAHS)患者的心率变异性(heart rate variability,HRV)特征。方法回顾性分析2018年4月至2022年5月在西安交通大学第二附属医院行多导睡眠(polysomnography,PSG)监测确诊为重度OSAHS的78例患者,根据身体质量(body mass index,BMI)将患者分为肥胖并重度OSAHS组(n=43)和非肥胖并重度OSAHS组(n=35)。所有患者行PSG监测同时接受24 h动态心电图监测,进行HRV指标的组间差异分析及与临床指标的相关性分析。结果基础指标及PSG指标分析结果显示,与非肥胖并重度OSAHS组相比,肥胖并重度OSAHS组体质量、BMI、颈围、腰围、呼吸暂停低通气指数(apnea hypopnea index,AHI)显著升高。组间HRV分析结果显示,与非肥胖并重度OSAHS组相比,肥胖并重度OSAHS组的24 h正常R-R间期标准差(standard deviation of R-R interval,SDNN)、5 min R-R间期均值标准差(standard deviation of the averages of 5-minute R-R intervals,SDANN)、三角指数(triangle index,TI)、心率减速力(deceleration capacity of heart rate,DC)、清醒期SDNN及睡眠高频功率明显降低(P<0.05)。相关性结果显示肥胖并重度OSAHS患者中相邻R-R间期差值均方根(root mean square of the difference of adjacent R-R interval,rMSSD)与高血压病程呈负相关,TI、DC与AHI呈负相关。经校正颈围和腰围后的线性回归分析显示SDNN、SDANN、rMSSD与收缩压相关(P<0.05)。结论肥胖并重度OSAHS患者存在HRV指标下降,自主神经功能受到损害,心血管疾病的发生风险增加。展开更多
文摘Obstructive sleep apnea syndrome (OSAS) is a common sleep disorder. It has been reported that approximately 40% of patients with moderate or severe OSAS die within the first eight years of disease. In hospitals, OSAS is inspected using polysomnography, which uses a number of sensors. Because of the cumbersome nature of this polysomnography, an initial OSAS screening is usually conducted. In recent years, OSAS screening techniques using Holter electrocardiogram (ECG) have been reported. However, the techniques so far reported cannot perform an OSAS severity assessment. The present study presents a new method to distinguish the obstructive sleep apnea (OSA) and non-OSA epochs at one-second intervals based on the Apnea Hypopnea Index assessment, defined as the duration of continuous apnea. In the proposed method, the time-frequency components of the heart rate variability and three ECG-derived respiration signals calculated by the complex Morlet wavelet transformation are adopted as features. A support vector machine is employed for classification. The proposed method is evaluated using three eight-hour ECG recordings containing OSA episodes from three subjects. As a result, the sensitivity and specificity of classification are found to reach approximately 90%, a level suitable for OSAS screening in clinical settings.
文摘目的探讨肥胖合并重度阻塞性睡眠呼吸暂停低通气综合征(obstructive sleep apnea hypopnea syndrome,OSAHS)患者的心率变异性(heart rate variability,HRV)特征。方法回顾性分析2018年4月至2022年5月在西安交通大学第二附属医院行多导睡眠(polysomnography,PSG)监测确诊为重度OSAHS的78例患者,根据身体质量(body mass index,BMI)将患者分为肥胖并重度OSAHS组(n=43)和非肥胖并重度OSAHS组(n=35)。所有患者行PSG监测同时接受24 h动态心电图监测,进行HRV指标的组间差异分析及与临床指标的相关性分析。结果基础指标及PSG指标分析结果显示,与非肥胖并重度OSAHS组相比,肥胖并重度OSAHS组体质量、BMI、颈围、腰围、呼吸暂停低通气指数(apnea hypopnea index,AHI)显著升高。组间HRV分析结果显示,与非肥胖并重度OSAHS组相比,肥胖并重度OSAHS组的24 h正常R-R间期标准差(standard deviation of R-R interval,SDNN)、5 min R-R间期均值标准差(standard deviation of the averages of 5-minute R-R intervals,SDANN)、三角指数(triangle index,TI)、心率减速力(deceleration capacity of heart rate,DC)、清醒期SDNN及睡眠高频功率明显降低(P<0.05)。相关性结果显示肥胖并重度OSAHS患者中相邻R-R间期差值均方根(root mean square of the difference of adjacent R-R interval,rMSSD)与高血压病程呈负相关,TI、DC与AHI呈负相关。经校正颈围和腰围后的线性回归分析显示SDNN、SDANN、rMSSD与收缩压相关(P<0.05)。结论肥胖并重度OSAHS患者存在HRV指标下降,自主神经功能受到损害,心血管疾病的发生风险增加。
