论文标题
基于睡眠脑电图的夜间到晚上的变异性
Night-to-Night Variability of Sleep Electroencephalography-Based Brain Age Measurements
论文作者
论文摘要
源自睡眠脑电图(EEG)计算的客观脑年龄指数(BAI)已被认为是脑健康的生物标志物。这项研究量化了BAI的夜间夜间变异性,并确定了基于患者BAI推断潜在脑病理学的概率阈值。 方法86例连续脑电图记录的患者是从癫痫监测单位患者中选择的,其脑电图报告为正常限制。使用先前描述的算法对每个12小时的患者数据进行计算BAI,并测量BAI的夜间变化。 结果BAI的住院内夜至晚上的标准偏差为7。5年。通过平均2、3和4晚来得出的BAI的估计分别为4.7、3.7和3.0年。 结论在N夜间平均BAI的结论可将BAI的夜间到晚上的变化减少到N的平方根,使BAI在单个水平上更适合作为脑健康的生物标志物。 BAI有可能跟踪脑部健康并检测出与正常生理功能的偏差的潜力,具有越来越多的EEG获取,包括可穿戴技术的意义。在临床环境中,BAI可用于识别应进行进一步研究或监测的患者。
Objective Brain Age Index (BAI), calculated from sleep electroencephalography (EEG), has been proposed as a biomarker of brain health. This study quantifies night-to-night variability of BAI and establishes probability thresholds for inferring underlying brain pathology based on a patient's BAI. Methods 86 patients with multiple nights of consecutive EEG recordings were selected from Epilepsy Monitoring Unit patients whose EEGs reported as being within normal limits. BAI was calculated for each 12-hour segment of patient data using a previously described algorithm, and night-to-night variability in BAI was measured. Results The within-patient night-to-night standard deviation in BAI was 7.5 years. Estimates of BAI derived by averaging over 2, 3, and 4 nights had standard deviations of 4.7, 3.7, and 3.0 years, respectively. Conclusions Averaging BAI over n nights reduces night-to-night variability of BAI by a factor of the square root of n, rendering BAI more suitable as a biomarker of brain health at the individual level. Significance With increasing ease of EEG acquisition including wearable technology, BAI has the potential to track brain health and detect deviations from normal physiologic function. In a clinical setting, BAI could be used to identify patients who should undergo further investigation or monitoring.