Scientific Reports (Jul 2024)

Sleep architecture in idiopathic hypersomnia: the influence of age, sex, and body mass index

  • Anne-Sophie Deshaies-Rugama,
  • Samantha Mombelli,
  • Hélène Blais,
  • Zoran Sekerovic,
  • MiaClaude Massicotte,
  • Cynthia Thompson,
  • Milan Nigam,
  • Julie Carrier,
  • Alex Desautels,
  • Jacques Montplaisir,
  • Nadia Gosselin

DOI
https://doi.org/10.1038/s41598-024-67203-6
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 11

Abstract

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Abstract This study aimed to progress the understanding of idiopathic hypersomnia (IH) by assessing the moderating influence of individual characteristics, such as age, sex, and body mass index (BMI) on sleep architecture. In this retrospective study, 76 IH participants (38.1 ± 11.3 years; 40 women) underwent a clinical interview, an in-laboratory polysomnography with a maximal 9-h time in bed and a multiple sleep latency test (MSLT). They were compared to 106 healthy controls (38.1 ± 14.1 years; 60 women). Multiple regressions were used to assess moderating influence of age, sex, and BMI on sleep variables. We used correlations to assess whether sleep variables were associated with Epworth Sleepiness Scale scores and mean sleep onset latency on the MSLT in IH participants. Compared to controls, IH participants had shorter sleep latency (p = 0.002), longer total sleep time (p < 0.001), more time spent in N2 sleep (p = 0.008), and showed trends for a higher sleep efficiency (p = 0.023) and more time spent in rapid eye movement (REM) sleep (p = 0.022). No significant moderating influence of age, sex, or BMI was found. More severe self-reported sleepiness in IH patients was correlated with shorter REM sleep latency and less N1 sleep in terms of proportion and duration (ps < 0.01). This study shows that, when compared to healthy controls, patients with IH had no anomalies in their sleep architecture that can explain their excessive daytime sleepiness. Moreover, there is no moderating influence of age, sex, and BMI, suggesting that the absence of major group differences is relatively robust.

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