Search

Study Objectives: Hypocretin deficient narcolepsy (type 1, NT1) presents with multiple sleep abnormalities including sleep-onset rapid eye movement (REM) periods (SOREMPs) and sleep fragmentation. We hypothesized that cortical arousals, as scored by an automatic detector, are elevated in NT1 and narcolepsy type 2 (NT2) patients as compared to control subjects., Methods: We analyzed nocturnal polysomnography (PSG) recordings from 25 NT1 patients, 20 NT2 patients, 18 clinical control subjects (CC, suspected central hypersomnia but with normal cerebrospinal (CSF) fluid hypocretin-1 (hcrt-1) levels and normal results on the multiple sleep latency test), and 37 healthy control (HC) subjects. Arousals were automatically scored using Multimodal Arousal Detector (MAD), a previously validated automatic wakefulness and arousal detector. Multiple linear regressions were used to compare arousal index (ArI) distributions across groups. Comparisons were corrected for age, sex, body-mass index, medication, apnea-hypopnea index, periodic leg movement index, and comorbid rapid eye movement sleep behavior disorder., Results: NT1 was associated with an average increase in ArI of 4.02 events/h (p = 0.0246) compared to HC and CC, while no difference was found between NT2 and control groups. Additionally, a low CSF hcrt-1 level was predictive of increased ArI in all the CC, NT2, and NT1 groups., Conclusions: The results further support the hypothesis that a loss of hypocretin neurons causes fragmented sleep, which can be measured as an increased ArI as scored by the MAD., (© Sleep Research Society 2020. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.)

Objective: Significant interscorer variability is found in manual scoring of arousals in polysomnographic recordings (PSGs). We propose a fully automatic method, the Multimodal Arousal Detector (MAD), for detecting arousals., Methods: A deep neural network was trained on 2,889 PSGs to detect cortical arousals and wakefulness in 1-second intervals. Furthermore, the relationship between MAD-predicted labels on PSGs and next day mean sleep latency (MSL) on a multiple sleep latency test (MSLT), a reflection of daytime sleepiness, was analyzed in 1447 MSLT instances in 873 subjects., Results: In a dataset of 1,026 PSGs, the MAD achieved an F1 score of 0.76 for arousal detection, while wakefulness was predicted with an accuracy of 0.95. In 60 PSGs scored by nine expert technicians, the MAD performed comparable to four and significantly outperformed five expert technicians for arousal detection. After controlling for known covariates, a doubling of the arousal index was associated with an average decrease in MSL of 40 seconds (p = 0.0075)., Conclusions: The MAD performed better or comparable to human expert scorers. The MAD-predicted arousals were shown to be significant predictors of MSL., Significance: This study validates a fully automatic method for scoring arousals in PSGs., Competing Interests: Declaration of Competing Interest Dr. Mignot has received funding from Jazz pharmaceutical and has shares in Rythm, a company doing a consumer portable EEG device, and Inoxia/Orexia, a company developing orexin agonists, but these involvements are unrelated to this project. Katie L. Stone has received grant funding from Merck, but this is unrelated to this project and they are not involved., (Copyright © 2020 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)