Gugger M
Dept of Medicine, University of Berne, Inselspital, Switzerland.
Eur Respir J. 1997 Mar;10(3):587-91.
In patients with the sleep apnoea/hypopnoea syndrome (SAHS), accurate and timely diagnostic evaluation and initiation of effective treatment is important. Therefore, an increasing number of limited sleep studies are now performed nowadays diagnosing the SAHS in typical patients. It was the aim of the present study to evaluate the diagnostic accuracy of one such system, the updated ResMed Sullivan AutoSet, against polysomnography. Sixty seven patients underwent full overnight polysomnography and simultaneous data acquisition with the AutoSet. Up to now, the AutoSet was designed for apnoea detection only. The new AutoSet, with software version 3.03, detects apnoeas if ventilation drops to <25%, and apnoeas+hypopnoeas if ventilation drops to <50%, compared with the recent average (100 s), using two independent detectors. A two page report with graphically displayed information on oximetry, snoring and breathing parameters, and an apnoea+hypopnoea index (AHI) and an apnoea index (AI) are provided at the end of each study night. There was a correlation between the AHI assessed by the AutoSet (AHI-AutoSet) and by polysomnography (AHI-PSG; r=0.95). The mean difference between the AHI-AutoSet minus the AHI-PSG was 4.2 (SD 7.2) respiratory events x h(-1) (p<0.001). The AutoSet identified patients with an AHI-PSG >20 events x h(-1) (a level of respiratory disturbance that would warrant consideration for treatment in most centres for sleep disorders), with a sensitivity of 97% and a specificity of 77%. The AutoSet was superior to oximetry alone. As event counting was similar between the two methods, the AHI-AutoSet may provide a reasonable indicator of the respiratory disturbance at night, especially when taking the patients graphic study report into consideration. In conjunction with full clinical information on the patients under investigation, the AutoSet might become a useful device in diagnosing the sleep apnoea/hypopnoea syndrome.
对于睡眠呼吸暂停/低通气综合征（SAHS）患者，准确及时的诊断评估以及启动有效治疗至关重要。因此，如今越来越多针对典型患者诊断SAHS的有限睡眠研究得以开展。本研究旨在评估一种此类系统——更新后的瑞思迈Sullivan AutoSet相对于多导睡眠图的诊断准确性。67例患者接受了整夜的多导睡眠图检查，并同时使用AutoSet进行数据采集。到目前为止，AutoSet仅设计用于呼吸暂停检测。新的AutoSet软件版本为3.03，使用两个独立的探测器，与最近的平均值（100秒）相比，当通气量降至<25%时检测呼吸暂停，当通气量降至<50%时检测呼吸暂停+低通气。每个研究夜晚结束时会提供一份两页的报告，以图形方式显示有关血氧饱和度、打鼾和呼吸参数的信息，以及呼吸暂停+低通气指数（AHI）和呼吸暂停指数（AI）。AutoSet评估的AHI（AHI-AutoSet）与多导睡眠图评估的AHI（AHI-PSG）之间存在相关性（r=0.95）。AHI-AutoSet减去AHI-PSG的平均差值为4.2（标准差7.2）次呼吸事件/小时（p<0.001）。AutoSet识别出AHI-PSG>20次事件/小时的患者（这一呼吸紊乱水平在大多数睡眠障碍中心会被视为需要考虑治疗），敏感性为97%，特异性为77%。AutoSet优于单独的血氧饱和度测定。由于两种方法的事件计数相似，AHI-AutoSet可能为夜间呼吸紊乱提供合理指标，尤其是考虑到患者的图形研究报告时。结合所研究患者的完整临床信息，AutoSet可能成为诊断睡眠呼吸暂停/低通气综合征的有用设备。
