J Sleep Med.  2020 Jun;17(1):31-36. 10.13078/jsm.190050.

Quantification of Rapid Eye Movement Sleep without Atonia to Diagnose Rapid Eye Movement Sleep Behavior Disorder: A Retrospective and Case-Control Study

Affiliations
  • 1Department of Neurology, Pusan National University School of Medicine, Busan, Korea
  • 2Sleep Disorders Center, Pusan National University Hospital, Busan, Korea

Abstract


Objectives
Rapid eye movement (REM) sleep without atonia (RSWA) fulfils one of the criteria for diagnosing REM sleep behavior disorder (RBD) according to the International Classification of Sleep Disorders, Third Edition. However, RSWA quantification is an unresolved issue, which is associated with the future direction of revising the diagnostic criteria. The purpose of this study was to evaluate the quantification of RSWA in patients with RBD and identify an optimal cut-off value of quantitative RSWA for RBD diagnosis.
Methods
Medical records and polysomnographic results were analyzed retrospectively to diagnose sleep disorders from June 2017 to May 2018 at Pusan National University Hospital. Nineteen subjects with idiopathic RBD were included in the present study. Propensity score matching was used to control age, gender, and anti-depressant factors, which influenced RSWA. RSWA was scored according to the American Academy of Sleep Medicine scoring manual. Cohen’s kappa coefficient was measured to test inter-rater reliability between two polysomnography raters.
Results
Cohen’s kappa coefficients were 0.755 (p<0.001) and 0.689 (p<0.001) for tonic and phasic activities, respectively. RSWA was significantly increased in subjects with RBD compared with controls [median and interquartile range: 16.5 (8.8–24.6) vs. 6.3 (4.1–7.2) p=0.001]. The optimal cut-off value was 8.0% for the proportion of RSWA (sensitivity 78.5%, specificity 85.7%, area under the receiver-operating characteristic curve 0.837).
Conclusions
Subjects with RBD had significantly increased RSWA compared to controls. The proportion of RSWA during REM sleep can be applied to discriminate subjects with RBD from controls.

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