"EMG variance during polysomnography as an assessment for REM sleep beh" by Joseph W. Burns, Flavia B. Consens et al.
 

Title

EMG variance during polysomnography as an assessment for REM sleep behavior disorder

Document Type

Article

Publication Date

12-2007

Abstract

Study Objectives:

In a previous study, we validated a polysomnographic assessment for REM sleep behavior disorder (RBD). The method proved to be reliable but required slow, labor-intensive visual scoring of surface electromyogram (EMG) activity. We therefore developed a computerized metric to assess EMG variance and compared the results to those previously published for visual scoring, bed partner-rated RBD symptom scores, and clinical assessments by sleep medicine specialists.

Design:

Retrospective validation of new computer algorithm

Setting:

Sleep research laboratory

Participants:

Twenty-three subjects: 17 with neurodegenerative disorders (9 with probable or possible RBD), and 6 controls.

Interventions:

N/A

Methods:

We visually scored 2 consecutive nocturnal polysomnograms for each subject. A computer algorithm calculated the variance of the chin EMG during all 3-second mini-epochs, and compared variances during REM sleep to a threshold defined by variances during quiet NREM sleep. The percentage of all REM mini-epochs with variance above this threshold created a metric, which we refer to as the supra-threshold REM EMG activity metric (STREAM) for each subject.

Results:

The STREAM correlated highly with the visually-derived score for RBD severity (Spearman rho = 0.87, P < 0.0001). A clinical impression of probable or possible RBD was associated to a similar extent with both STREAM (Wilcoxon rank sum test, P = 0.009) and the visually-derived score (P = 0.018). An optimal STREAM cutoff identified probable or possible RBD with 100% sensitivity and 71% specificity. The RBD symptom score correlated with both STREAM (rho = 0.42, P = 0.046) and the visual score (rho = 0.42, P = 0.048).

Conclusions:

These results suggest that a new, automated assessment for RBD may provide as much utility as a more time-consuming manual approach.

Publisher's Statement

© 2007 American Academy of Sleep Medicine. Publisher's version of record: http:/doi.org/10.1093/sleep/30.12.1771

Publication Title

Sleep

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