Night-to-night variability of automatic quantitative parameters of the chin EMG amplitude (atonia index) in REM sleep behavior disorder

Abstract

STUDY OBJECTIVES: To analyze the night-to-night variability of REM sleep electromyographic (EMG) features of REM sleep behavior disorder (RBD) by using the automatic quantitative method known as atonia index (AI), and to evaluate the improvement in sensitivity and specificity of AI for the diagnosis of RBD when a second recording night is available. SETTING: Sleep research center. INTERVENTIONS: N/A. METHODS: A group of 17 idiopathic RBD patients was recruited for whom 2 all-night polysomnographic (PSG) recordings were available. Thirty normal controls were also recruited and subgrouped into Young (< 45 years of age) or Aged (> 45 years). Chin EMG analysis was run on all recordings; night-to-night variability of both AI and number of chin EMG activations/h during REM sleep was additionally quantified as the absolute difference between the 2 nights standardized as the percentage of their mean. MEASUREMENTS AND RESULTS: Night-to-night variability of AI was higher in RBD patients (19.7%) than in the 2 groups of controls (Young 1.8% and Aged 2.8%). The values of variability of chin EMG activations were much higher than those of AI, especially in the Aged controls. Sensitivity of AI ≤ 0.9 for RBD was always higher than 82% and reached 88.9% for the combined-night analysis; specificity was also high, with a value of 92.3% for the combined-value analysis. CONCLUSION: The night-to-night variability of AI seems to be very low in normal controls and remains under 20% in RBD patients; that of the number of EMG activations is higher. However, even a single PSG recording provides high values of sensitivity and specificity when a threshold value of AI ≤ 0.9 is used to define abnormal chin EMG levels during REM sleep that increase only moderately when a second night recording is available.