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 within normal limits. While EEGs with epileptiform activity were excluded, the majority of patients included in the study had a diagnosis of chronic epilepsy. BAI was calculated for each 12-hour segment of patient data using a previously established algorithm, and the 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 n, rendering BAI a more suitable biomarker of brain health at the individual level. A brain age risk lookup table of results provides thresholds above which a patient has a high probability of excess BAI. 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. The measure of night-to-night variability and how this is reduced by averaging across multiple nights provides a basis for using BAI in patients' homes to identify patients who should undergo further investigation or monitoring.

中文翻译：

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基于睡眠脑电图的大脑年龄测量的夜间变异性


目的 根据睡眠脑电图 (EEG) 计算得出的脑年龄指数 (BAI) 已被提议作为大脑健康的生物标志物。这项研究量化了 BAI 的夜间变异性，并建立了根据患者 BAI 推断潜在大脑病理学的概率阈值。方法 从癫痫监测中心的患者中选出 86 名连续多晚进行脑电图记录的患者，其脑电图报告在正常范围内。虽然排除了具有癫痫样活动的脑电图，但该研究中的大多数患者都被诊断为慢性癫痫。使用先前建立的算法计算每个 12 小时患者数据段的 BAI，并测量 BAI 的夜间变异性。结果 患者体内 BAI 的每晚标准差为 7.5 年。通过平均 2、3 和 4 晚得出的 BAI 估计值的标准差分别为 4.7、3.7 和 3.0 年。结论 对 n 晚的 BAI 进行平均，可以将 BAI 的夜间变异性降低 n 倍，使 BAI 成为个体水平上更合适的大脑健康生物标志物。脑年龄风险结果查找表提供了阈值，高于该阈值的患者 BAI 过量的可能性很高。意义 随着脑电图采集（包括可穿戴技术）变得越来越容易，BAI 有潜力跟踪大脑健康并检测正常生理功能的偏差。夜间变异性的测量以及如何通过对多个夜晚进行平均来降低变异性，为在患者家中使用 BAI 来识别应接受进一步调查或监测的患者提供了基础。