Probabilistic Sleep Staging in MSLTs across Hypersomnia Disorders.
hypersomnia
machine learning
microsleep
mslt
narcolepsy
Journal
Sleep
ISSN: 1550-9109
Titre abrégé: Sleep
Pays: United States
ID NLM: 7809084
Informations de publication
Date de publication:
11 Oct 2024
11 Oct 2024
Historique:
received:
01
03
2024
medline:
11
10
2024
pubmed:
11
10
2024
entrez:
11
10
2024
Statut:
aheadofprint
Résumé
This study aimed to identify novel markers of narcolepsy type 1 (NT1) using between-nap opportunity periods ('Lights On') and in-nap opportunity periods ('Lights Off') features of Multiple Sleep Latency Test (MSLT) recordings. We hypothesized that NT1 could be identified both from sleep-wake instability and patterns of sleepiness during wakefulness. Further, we explored if MSLTs from NT1 and narcolepsy type 2 (NT2) patients could be distinguished despite having the same diagnostic thresholds. We analyzed 'Lights On' and 'Lights Off' periods of the MSLT, extracting 163 features describing sleepiness, microsleep, and sleep stage mixing using data from 177 patients with NT1, NT2, Idiopathic Hypersomnia (IH), and Subjective Hypersomnia (sH) from three sleep centers. These features were based on automated probabilistic sleep staging, also denoted as hypnodensities, using U-Sleep. Hypersomnias were differentiated using either or both features from 'Lights On' and 'Lights Off'. Patients with NT1 could be distinguished from NT2, IH, and sH using features solely from 'Lights On' periods with a sensitivity of 0.76 and specificity of 0.71. When using features from all periods of the MSLT, NT1 was distinguished from NT2 alone with a sensitivity of 0.77 and a specificity of 0.84. The findings of this study demonstrate microsleeps and sleep stage mixing as potential markers of the sleep attacks and unstable sleep-wake states common in NT1. Further, NT1 and NT2 could be frequently distinguished using 'Lights Off' features.
Identifiants
pubmed: 39392922
pii: 7818427
doi: 10.1093/sleep/zsae241
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© The Author(s) 2024. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.