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一种用于睡眠呼吸暂停患者睡眠-觉醒评估的新型自适应手腕活动记录仪算法。

A novel adaptive wrist actigraphy algorithm for sleep-wake assessment in sleep apnea patients.

作者信息

Hedner Jan, Pillar Giora, Pittman Stephen D, Zou Ding, Grote Ludger, White David P

机构信息

Sleep Laboratory, Pulmonary Medicine, Sahlgrenska University Hospital, Gothenburg, Sweden.

出版信息

Sleep. 2004 Dec 15;27(8):1560-6. doi: 10.1093/sleep/27.8.1560.

Abstract

STUDY OBJECTIVES

Current actigraphic algorithms are relatively less accurate in detecting sleep and wake in sleep apnea patients than in people without sleep apnea. In the current study, we attempted to validate a novel automatic algorithm, which was developed for actigraphic studies in normal subjects and patients with obstructive sleep apnea by comparing it on an epoch-by-epoch basis to standard polysomnography.

DESIGN

Prospective cohort study.

SETTING

Multicenter, university hospital, sleep laboratories.

PARTICIPANTS

A total of 228 subjects from 3 different sleep centers (Skara, Boston, Haifa) participated.

INTERVENTION AND MEASUREMENTS

Simultaneous recording of polysomnography and Watch_PAT100, an ambulatory device that contains a built-in actigraph. The automatic sleep/wake algorithm is based on both the quantification of motion (magnitude and duration) and the various periodic movement patterns, such as those occurring in patients with moderate to severe obstructive sleep apnea.

RESULTS

The overall sensitivity and specificity to identify sleep was 89% and 69%, respectively. The agreement ranged from 86% in the normal subjects to 86%, 84%, and 80% in the patients with mild, moderate, and severe obstructive sleep apnea, respectively. There was a tight agreement between actigraphy and polysomnography in determining sleep efficiency (78.4 +/- 9.9 vs 78.8 +/- 13.4%), total sleep time (690 +/- 152 vs 690 +/- 154 epochs), and sleep latency (56.8 +/- 31.4 vs 43.3 +/- 45.4 epochs). While for most individuals the difference between the polysomnography and actigraphy was relatively small, for some there was a substantial disagreement.

CONCLUSIONS

We conclude that this actigraphy algorithm provides a reasonably accurate estimation of sleep and wakefulness in normal subjects and patients with obstructive sleep apnea on an epoch-by-epoch basis. This simple method for assessment of total sleep time may provide a useful tool for the accurate quantification of obstructive sleep apnea in the home environment.

摘要

研究目的

与无睡眠呼吸暂停的人群相比,目前的活动记录仪算法在检测睡眠呼吸暂停患者的睡眠和清醒状态时准确性相对较低。在本研究中,我们试图验证一种新的自动算法,该算法是为正常受试者和阻塞性睡眠呼吸暂停患者的活动记录仪研究而开发的,通过逐段与标准多导睡眠图进行比较来验证。

设计

前瞻性队列研究。

设置

多中心大学医院睡眠实验室。

参与者

来自3个不同睡眠中心(斯卡拉、波士顿、海法)的228名受试者参与研究。

干预与测量

同时记录多导睡眠图和Watch_PAT100,这是一种包含内置活动记录仪的便携式设备。自动睡眠/清醒算法基于运动的量化(幅度和持续时间)以及各种周期性运动模式,如中重度阻塞性睡眠呼吸暂停患者出现的运动模式。

结果

识别睡眠的总体敏感性和特异性分别为89%和69%。一致性范围从正常受试者的86%到轻度、中度和重度阻塞性睡眠呼吸暂停患者的86%、84%和80%。在确定睡眠效率(78.4±9.9%对78.8±13.4%)、总睡眠时间(690±152对690±154个时段)和睡眠潜伏期(56.8±31.4对43.3±45.4个时段)方面,活动记录仪和多导睡眠图之间存在紧密一致性。虽然对大多数个体而言,多导睡眠图和活动记录仪之间的差异相对较小,但对一些个体而言存在显著差异。

结论

我们得出结论,这种活动记录仪算法在逐段基础上为正常受试者和阻塞性睡眠呼吸暂停患者的睡眠和清醒状态提供了合理准确的估计。这种评估总睡眠时间的简单方法可能为在家中准确量化阻塞性睡眠呼吸暂停提供一个有用的工具。

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