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首页> 外文期刊>Journal of sleep research >Objective markers for sleep propensity: comparison between the Multiple Sleep Latency Test and the Vigilance Algorithm Leipzig
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Objective markers for sleep propensity: comparison between the Multiple Sleep Latency Test and the Vigilance Algorithm Leipzig

机译：睡眠倾向的客观指标：多重睡眠潜伏期测试与警惕性算法莱比锡之间的比较

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摘要

The regulation of wakefulness is important for high-order organisms. Itsdysregulation is involved in the pathomechanism of several psychiatric disorders. Thus, a tool for its objective but little time-consuming assessment would be of importance. The Vigilance Algorithm Leipzig allows the objective measurement of sleep propensity, based on a single resting state electroencephalogram. To compare the Vigilance Algorithm Leipzig with the standard for objective assessment of excessive daytime sleepiness, a four-trial Multiple Sleep Latency Test in 25 healthy subjects was conducted. Between the first two trials, a 15-min, 25-channel restingelectroencephalogram was recorded, and Vigilance Algorithm Leipzig was used to classify the sleep propensity (i.e. type of vigilance regulation) of each subject. The results of both methods showed significant correlations with the Epworth Sleepiness Scale (=-0.70; =0.45, respectively) and correlated with each other (=-0.54). Subjects with a stable electroencephalogram-vigilance regulation yielded significant increased sleep latencies compared with an unstable regulation (multiple sleep latency 898.5s versus 549.9s; P=0.03). Further, Vigilance Algorithm Leipzig classifications allowed the identification of subjects with average sleep latencies <6min with a sensitivity of 100% and a specificity of 77%. Thus, Vigilance Algorithm Leipzig provides similar information on wakefulness regulation in comparison to the much more cost- and time-consuming Multiple Sleep Latency Test. Due to its high sensitivity and specificity for large sleep propensity, Vigilance Algorithm Leipzig could be an effective and reliable alternative to the Multiple Sleep Latency Test, for example for screening purposes in large cohorts, where objective information about wakefulness regulation is needed.
机译：唤醒的调节对于高阶生物很重要。它的调节失调与几种精神疾病的发病机制有关。因此，进行客观但耗时很少的评估的工具将很重要。莱比锡警惕算法可基于单个静止状态脑电图客观地测量睡眠倾向。为了比较莱比锡警惕算法与客观评估白天过度嗜睡的标准，在25名健康受试者中进行了四次试验多次睡眠延迟测试。在前两次试验之间，记录了15分钟，25通道的静息脑电图，并使用警惕算法莱比锡对每个受试者的睡眠倾向（即警觉调节类型）进行分类。两种方法的结果均显示出与Epworth嗜睡量表的显着相关性（分别为= -0.70; = 0.45），并且彼此相关（= -0.54）。与不稳定的调节相比，具有稳定的脑电图警觉性调节的受试者产生了显着增加的睡眠潜伏期（多个睡眠潜伏期898.5s对549.9s; P = 0.03）。此外，警惕性算法莱比锡分类可以识别平均睡眠潜伏期<6min的受试者，其敏感性为100％，特异性为77％。因此，与耗费更多时间和成本的多重睡眠延迟测试相比，警惕算法莱比锡提供了类似的唤醒调节信息。由于对大型睡眠倾向具有高度的敏感性和特异性，因此警惕性莱比锡算法可以作为多睡眠潜伏期测试的一种有效且可靠的替代方法，例如用于大型队列中的筛查目的，在该队列中需要有关清醒调节的客观信息。

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