Department of Medicine, Harvard University, Boston, MA, USA.
Sleep. 2013 Apr 1;36(4):573-82. doi: 10.5665/sleep.2548.
Manual scoring of polysomnograms (PSG) is labor intensive and has considerable variance between scorers. Automation of scoring could reduce cost and improve reproducibility. The purpose of this study was to compare a new automated scoring system (YST-Limited, Winnipeg, Canada) with computer-assisted manual scoring.
Technical assessment.
Five academic medical centers.
N/A.
N/A.
Seventy PSG files were selected at University of Pennsylvania (Penn) and distributed to five US academic sleep centers. Two blinded technologists from each center scored each file. Automatic scoring was performed at Penn by a YST Limited technician using a laptop containing the software. Variables examined were sleep stages, arousals, and apnea-hypopnea index (AHI) using three methods of identifying hypopneas. Automatic scores were not edited and were compared to the average scores of the 10 technologists. Intraclass correlation coefficient (ICC) was obtained for the 70 pairs and compared to across-sites ICCs for manually scored results. ICCs for automatic versus manual scoring were > 0.8 for total sleep time, stage N2, and nonrapid eye movement arousals and > 0.9 for AHI scored by primary and secondary American Academy of Sleep Medicine criteria. ICCs for other variables were not as high but were comparable to the across-site ICCs for manually scored results.
The automatic system yielded results that were similar to those obtained by experienced technologists. Very good ICCs were obtained for many primary PSG outcome measures. This automated scoring software, particularly if supplemented with manual editing, may increase laboratory efficiency and standardize PSG scoring results within and across sleep centers.
手动评分多导睡眠图(PSG)需要大量的劳动力,并且评分者之间存在很大的差异。评分自动化可以降低成本并提高可重复性。本研究的目的是比较一种新的自动评分系统(加拿大温尼伯的 YST-Limited)与计算机辅助手动评分。
技术评估。
五个学术医疗中心。
无。
无。
从宾夕法尼亚大学(Penn)选择了 70 个 PSG 文件,并分发给五个美国学术睡眠中心。每个中心的两名盲法技术员对每个文件进行评分。宾夕法尼亚大学的一名 YST Limited 技术员使用包含该软件的笔记本电脑自动进行评分。使用三种识别低通气的方法检查变量睡眠阶段、觉醒和呼吸暂停低通气指数(AHI)。自动评分未经过编辑,并与 10 名技术员的平均评分进行比较。获得了 70 对的组内相关系数(ICC),并与手动评分结果的跨站点 ICC 进行了比较。自动与手动评分的 ICC 对于总睡眠时间、N2 期和非快速眼动觉醒均>0.8,对于主要和次要美国睡眠医学学会标准评分的 AHI 均>0.9。其他变量的 ICC 虽然不如手动评分结果的跨站点 ICC 高,但可与之相媲美。
自动系统产生的结果与经验丰富的技术员获得的结果相似。许多主要 PSG 结果测量得到了非常好的 ICC。这种自动评分软件,特别是如果辅以手动编辑,可能会提高实验室效率,并在睡眠中心内部和之间标准化 PSG 评分结果。