Patel Sanjay R, Weng Jia, Rueschman Michael, Dudley Katherine A, Loredo Jose S, Mossavar-Rahmani Yasmin, Ramirez Maricelle, Ramos Alberto R, Reid Kathryn, Seiger Ashley N, Sotres-Alvarez Daniela, Zee Phyllis C, Wang Rui
Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA.
Beth Israel Deaconess Medical Center, Boston, MA.
Sleep. 2015 Sep 1;38(9):1497-503. doi: 10.5665/sleep.4998.
While actigraphy is considered objective, the process of setting rest intervals to calculate sleep variables is subjective. We sought to evaluate the reproducibility of actigraphy-derived measures of sleep using a standardized algorithm for setting rest intervals.
Observational study.
Community-based.
A random sample of 50 adults aged 18-64 years free of severe sleep apnea participating in the Sueño sleep ancillary study to the Hispanic Community Health Study/Study of Latinos.
N/A.
Participants underwent 7 days of continuous wrist actigraphy and completed daily sleep diaries. Studies were scored twice by each of two scorers. Rest intervals were set using a standardized hierarchical approach based on event marker, diary, light, and activity data. Sleep/wake status was then determined for each 30-sec epoch using a validated algorithm, and this was used to generate 11 variables: mean nightly sleep duration, nap duration, 24-h sleep duration, sleep latency, sleep maintenance efficiency, sleep fragmentation index, sleep onset time, sleep offset time, sleep midpoint time, standard deviation of sleep duration, and standard deviation of sleep midpoint. Intra-scorer intraclass correlation coefficients (ICCs) were high, ranging from 0.911 to 0.995 across all 11 variables. Similarly, inter-scorer ICCs were high, also ranging from 0.911 to 0.995, and mean inter-scorer differences were small. Bland-Altman plots did not reveal any systematic disagreement in scoring.
With use of a standardized algorithm to set rest intervals, scoring of actigraphy for the purpose of generating a wide array of sleep variables is highly reproducible.
虽然活动记录仪被认为是客观的,但设置休息间隔以计算睡眠变量的过程是主观的。我们试图使用一种标准化算法来设置休息间隔,以评估活动记录仪得出的睡眠测量值的可重复性。
观察性研究。
基于社区。
从参与西班牙裔社区健康研究/拉丁裔研究的苏尼奥睡眠辅助研究的50名18 - 64岁无严重睡眠呼吸暂停的成年人中随机抽取。
无。
参与者进行了7天的连续手腕活动记录,并完成每日睡眠日记。两名评分者分别对研究进行两次评分。休息间隔采用基于事件标记、日记、光线和活动数据的标准化分层方法设置。然后使用经过验证的算法为每个30秒时段确定睡眠/清醒状态,并用于生成11个变量:平均夜间睡眠时间、午睡时间、24小时睡眠时间、睡眠潜伏期、睡眠维持效率、睡眠碎片化指数、入睡时间、起床时间、睡眠中点时间、睡眠时间标准差和睡眠中点标准差。评分者内组内相关系数(ICC)很高,在所有11个变量中范围为0.911至0.995。同样,评分者间ICC也很高,范围也为0.911至0.995,评分者间平均差异很小。Bland - Altman图未显示评分中有任何系统性差异。
使用标准化算法设置休息间隔时,为生成一系列睡眠变量而对活动记录仪进行评分具有高度可重复性。