Evaluation of hypersomnolence: From symptoms to diagnosis, a multidimensional approach
Langue
EN
Article de revue
Ce document a été publié dans
Revue Neurologique. 2023-10, vol. 179, n° 7, p. 715-726
Résumé en anglais
Hypersomnolence is a major public health issue given its high frequency, its impact on academic/occupational functioning and on accidentology, as well as its heavy socio-economic burden. The positive and aetiological ...Lire la suite >
Hypersomnolence is a major public health issue given its high frequency, its impact on academic/occupational functioning and on accidentology, as well as its heavy socio-economic burden. The positive and aetiological diagnosis is crucial, as it determines the therapeutic strategy. It must consider the following aspects: i) hypersomnolence is a complex concept referring to symptoms as varied as excessive daytime sleepiness, excessive need for sleep, sleep inertia, or drowsiness, all of which warrant specific dedicated investigations; ii) the boundary between physiological and abnormal hypersomnolence is blurred, since most symptoms can be encountered in the general population to varying degrees without being considered as pathological, meaning that their severity, frequency, context of occurrence and related impairment need to be carefully assessed; iii) investigation of hypersomnolence relies on scales/questionnaires as well as behavioural and neurophysiological tests, which measure one or more dimensions, keeping in mind the possible discrepancy between objective and subjective assessment; iv) aetiological reasoning is driven by knowledge of the main sleep regulation mechanisms, epidemiology, and associated symptoms. The need to assess hypersomnolence is growing, both for its management, and for assessing the efficacy of treatments. The landscape of tools available for investigating hypersomnolence is constantly evolving, in parallel with research into sleep physiology and technical advances. These investigations face the challenges of reconciling subjective perception and objective data, making tools accessible to as many people as possible and predicting the risk of accidents.< Réduire
Mots clés en anglais
Drowsiness
Hypersomnolence
Investigation
Polysomnography
Sleep inertia
Sleepiness
Unités de recherche