Department of Neurology, Leiden University Medical Centre, Leiden, The Netherlands.
PLoS One. 2013 Aug 5;8(8):e71234. doi: 10.1371/journal.pone.0071234. Print 2013.
Human sleep depth was traditionally assessed by scoring electro-encephalographic slow-wave amplitudes at the globally standardized C4-M1 electrode derivation. Since 2007, the American Association of Sleep Medicine (AASM) has accepted three additional derivations for the same purpose. These might well differ in slow wave amplitudes which would bias the scorings. Some derivations might also introduce large inter-individual variability. We compared mean and variability of slow wave amplitudes between six derivations including the four AASM ones. Slow wave amplitudes in those derivations were simultaneously measured using automated analysis in 29 patients. Each amplitude was divided by the average from the six derivations, thus removing shared factors such as age, gender and sleep depth while retaining factors that differ between the derivations such as caused by local skull characteristics, electrode distance and neuronal dipole orientation. The remaining inter-individual variability differed significantly and up to a factor of two between the AASM derivations. The amplitudes differed significantly and up to 60% between the AASM derivations, causing substantial scoring bias between centres using different derivations. The resulting de-standardization most likely affects any patient group because the amplitude differences were consistent over diagnoses, genders, and age. Derivation-dependent amplitude thresholds were proposed to reduce the scoring bias. However, it would be better to settle on just one derivation, for instance Cz-Oz or Fpz-Cz because these have lowest variability while matching the traditional C4-M1 amplitudes.
传统上,通过对全球标准化 C4-M1 电极推导的脑电图慢波幅度进行评分来评估人类的睡眠深度。自 2007 年以来,美国睡眠医学协会 (AASM) 已接受了另外三个用于相同目的的推导。这些推导可能在慢波幅度上存在差异,从而导致评分偏差。一些推导也可能引入较大的个体间变异性。我们比较了包括四个 AASM 推导在内的六个推导之间的慢波幅度的平均值和变异性。在 29 名患者中,使用自动分析同时测量了这些推导中的慢波幅度。每个幅度除以六个推导的平均值,从而消除了年龄、性别和睡眠深度等共同因素,同时保留了推导之间的差异因素,例如由局部颅骨特征、电极距离和神经元偶极子方向引起的差异。剩余的个体间变异性在 AASM 推导之间差异显著,最高可达两倍。幅度在 AASM 推导之间差异显著,最高可达 60%,导致使用不同推导的中心之间存在大量评分偏差。这种去标准化很可能影响任何患者群体,因为幅度差异在诊断、性别和年龄上都是一致的。提出了依赖推导的幅度阈值来减少评分偏差。但是,最好只使用一个推导,例如 Cz-Oz 或 Fpz-Cz,因为它们的变异性最低,同时与传统的 C4-M1 幅度匹配。