Stefani Ambra, Heidbreder Anna, Brandauer Elisabeth, Guaita Marc, Neier Lisa-Marie, Mitterling Thomas, Santamaria Joan, Iranzo Alex, Videnovic Aleksander, Trenkwalder Claudia, Sixel-Döring Friederike, Wenning Gregor K, Chade Anabel, Poewe Werner, Gershanik Oscar S, Högl Birgit
Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria.
Neurology Service, Hospital Clinic de Barcelona, IDIBAPS, CIBERNED, Barcelona, Spain.
Sleep. 2018 Jun 1;41(6). doi: 10.1093/sleep/zsy053.
To evaluate the utility of multimodal low-cost approaches including actigraphy, a wrist-worn device monitoring rest/activity cycles, in identifying patients with idiopathic REM sleep behavior disorder (iRBD).
Seventy patients diagnosed with sleep disorders causing different motor manifestations during sleep (iRBD, sleep apnea, restless legs syndrome) and 20 subjects without any relevant motor manifestation during sleep, underwent video-polysomnography (vPSG) and 2 week actigraphy, completed six validated RBD screening questionnaires, and sleep apps use was assessed. Actigraphy was analyzed automatically, and visually by seven blinded sleep medicine experts who rated as "no," "possible," and "probable" RBD.
Quantitative actigraphy analysis distinguished patients from controls, but not between patients with different types of motor activity during sleep. Visual actigraphy rating by blinded experts in sleep medicine using pattern recognition identified vPSG confirmed iRBD with 85%-95% sensitivity, 79%-91% specificity, 81%-91% accuracy, 57.7% ± 11.3% positive predictive value, 95.1% ± 3.3% negative predictive value, 6.8 ± 2.2 positive likelihood ratio, 0.14 ± 0.05 negative likelihood ratio and 0.874-0.933 area under the ROC curve (AUC). AUC of the best performing questionnaire was 0.868. Few patients used sleep apps; therefore, their potential utility in the evaluated patients' groups is limited.
Visual analysis of actigraphy using pattern recognition can identify subjects with iRBD, and is able to distinguish iRBD from other motor activities during sleep, even when patients are not aware of the disease in contrast to questionnaires. Therefore, actigraphy can be a reliable screening instrument for RBD potentially useful in the general population.
评估多模式低成本方法（包括活动记录仪，一种监测休息/活动周期的腕戴设备）在识别特发性快速眼动睡眠行为障碍（iRBD）患者中的效用。
70例被诊断为睡眠障碍且睡眠期间有不同运动表现的患者（iRBD、睡眠呼吸暂停、不宁腿综合征）以及20例睡眠期间无任何相关运动表现的受试者，接受了视频多导睡眠图（vPSG）和为期2周的活动记录仪监测，完成了6份经过验证的RBD筛查问卷，并评估了睡眠应用程序的使用情况。活动记录仪数据进行自动分析，并由7名不知情的睡眠医学专家进行视觉分析，他们将RBD评为“无”“可能”和“很可能”。
定量活动记录仪分析能够区分患者与对照组，但无法区分睡眠期间有不同类型运动活动的患者。不知情的睡眠医学专家使用模式识别对活动记录仪进行视觉评级，识别出vPSG确诊的iRBD，其敏感度为85%-95%，特异度为79%-91%，准确度为81%-91%，阳性预测值为57.7%±11.3%，阴性预测值为95.1%±3.3%，阳性似然比为6.8±2.2，阴性似然比为0.14±0.05，曲线下面积（AUC）为0.874-0.933。表现最佳的问卷的AUC为0.868。很少有患者使用睡眠应用程序；因此，其在评估患者群体中的潜在效用有限。
使用模式识别对活动记录仪进行视觉分析能够识别iRBD患者，并且能够将iRBD与睡眠期间的其他运动活动区分开来，即使患者与问卷调查情况不同，未意识到自身疾病。因此，活动记录仪可以成为一种可靠的RBD筛查工具，可能对普通人群有用。
