The aim of the present study was to examine gender and age-specific effects on subjective daytime sleepiness (as measured by the Epworth Sleepiness Scale), body weight and eating behaviour in patients with central disorders of hypersomnolence. Based on the European Narcolepsy Network database, we compared 1035 patients with narcolepsy type I and 505 patients with other central disorders of hypersomnolence ("narcoleptic borderland"), including narcolepsy type II (N = 308) and idiopathic hypersomnia (N = 174), using logistic regression and general linear models. In the entire study population, the Epworth Sleepiness Scale was higher in women (N = 735, mean age = 30 years, mean Epworth Sleepiness Scale = 16.6 ± SD 3.9) than in men (N = 805, mean age = 32 years, mean Epworth Sleepiness Scale = 15.8 ± SD 4.4). In women with narcolepsy type I (N = 475), both Epworth Sleepiness Scale and body mass index increased in parallel with age. In women of the narcoleptic borderland (N = 260), the Epworth Sleepiness Scale markedly peaked in their early 30s, while body mass index only started to rise at that age. This rise in body mass index following the Epworth Sleepiness Scale peak cannot be explained by sleepiness-induced uncontrolled eating, as self-reported uncontrolled eating was negatively associated with the Epworth Sleepiness Scale in this group. We propose that the narcoleptic borderland harbours a unique cluster of women in their fertile years with an unexplored aetiology requiring further investigation towards tailored interventions.

• Keywords
• excessive daytime sleepiness, hypersomnia, impulsive eating behaviour, obesity, sex,
• MeSH
• Adult MeSH
• Body Mass Index * MeSH
• Middle Aged MeSH
• Humans MeSH
• Adolescent MeSH
• Young Adult MeSH
• Narcolepsy * physiopathology   MeSH
• Disorders of Excessive Somnolence * physiopathology   epidemiology   MeSH
• Sex Factors MeSH
• Feeding Behavior MeSH
• Body Weight MeSH
• Age Factors MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Adolescent MeSH
• Young Adult MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

Fatigue, depression, and sleep inertia are frequently underdiagnosed manifestations in narcolepsy and idiopathic hypersomnia. Our cross-sectional study design included diagnostic interview accompanied by assessment instruments and aimed to explore how these factors influence disease severity as well as to elucidate any sex predisposition. One hundred and forty-eight subjects (female 63%) were divided into narcolepsy type 1 (NT1; n = 87, female = 61%), narcolepsy type 2 (NT2; n = 22, female = 59%), and idiopathic hypersomnia (IH; n = 39, female = 69%). All subjects completed a set of questionnaires: Epworth Sleepiness Scale (ESS), Hospital Anxiety and Depression Scales (HADS), Fatigue Severity Scale (FSS), and Sleep Inertia Questionnaire (SIQ). In narcoleptic subjects, questionnaire data were correlated with the Narcolepsy Severity Scale (NSS), and in subjects with idiopathic hypersomnia, with the Idiopathic Hypersomnia Severity Scale (IHSS). The highest correlation in narcoleptic subjects was found between NSS and ESS (r = 0.658; p < 0.0001), as well as FSS (r = 0.506; p < 0.0001), while in subjects with idiopathic hypersomnia, the most prominent positive correlations were found between IHSS and SIQ (r = 0.894; p < 0.0001), FSS (r = 0.812; p < 0.0001), HADS depression scale (r = 0.649; p = 0.0005), and HADS anxiety scale (r = 0.528; p < 0.0001). ESS showed an analogic correlation with disease severity (r = 0.606; p < 0.0001). HADS anxiety and depression scores were higher in females (p < 0.05 and p < 0.01), with similar results for FSS and SIQ scales (p < 0.05 for both), and a trend toward higher ESS values in females (p = 0.057). Our study illustrates that more attention should be focused on pathophysiological mechanisms and associations of fatigue, depression, as well as sleep inertia in these diseases; they influence the course of both illnesses, particularly in women.

• Keywords
• depression, disease severity, excessive daytime sleepiness, fatigue, idiopathic hypersomnia, narcolepsy type 1 and 2, sex differences, sleep inertia,
• Publication type
• Journal Article MeSH

PURPOSE: To report the efficacy and safety of lower-sodium oxybate (LXB; Xywav®) during the open-label titration and optimization period (OLT) and stable-dose period (SDP) in a clinical study for the treatment of idiopathic hypersomnia. PATIENTS AND METHODS: Data were collected during treatment titration and optimization in a phase 3 randomized withdrawal trial in adults (18-75 years of age) with idiopathic hypersomnia who took LXB treatment (once, twice, or thrice nightly, administered orally) in the OLT (10-14 weeks), followed by the 2-week, open-label SDP. Endpoints included the Epworth Sleepiness Scale (ESS), Idiopathic Hypersomnia Severity Scale (IHSS), Patient Global Impression of Change, Clinical Global Impression of Change, Functional Outcomes of Sleep Questionnaire (FOSQ)-10, and Work Productivity and Activity Impairment Questionnaire: Specific Health Problem (WPAI:SHP). RESULTS: The safety population included 154 participants; the modified intent-to-treat population comprised 115 participants. During open-label treatment, mean (SD) ESS scores improved (decreased) from 15.7 (3.8) at baseline to 6.1 (4.0) at end of SDP, and IHSS scores improved (decreased) from 31.6 (8.3) to 15.3 (8.5). Improvements were also observed during OLT in each individual IHSS item and in FOSQ-10 and WPAI:SHP scores. Thirty-five (22.7%) participants discontinued during OLT and SDP, 22 (14.3%) due to treatment-emergent adverse events (TEAEs) during OLT and SDP. The most frequent TEAEs in the first 4 weeks were nausea, headache, dizziness, and dry mouth; TEAE incidence decreased throughout OLT and SDP (weeks 1-4, n = 87 [56.5%]; weeks 13-16, n = 39 [31.7%]). CONCLUSION: During open-label treatment with LXB, participants showed clinically meaningful improvements in idiopathic hypersomnia symptoms and in quality of life and functional measures. TEAE incidence declined over LXB titration and optimization.

• Keywords
• excessive daytime sleepiness, hypersomnolence, pharmacotherapy, quality of life,
• Publication type
• Journal Article MeSH

AIMS OF THE STUDY: Commonly used approach to illness assessment focuses on the patient's actual state supplemented by binary records of past events and conditions. This research project was designed to explain subjective experience in idiopathic hypersomnia (IH) patients influenced by their clinical symptoms and comorbidities. MATERIAL AND METHODS: Forty-three IH patients of both sexes (female 60.5%, male 39.5%) were assessed using a detailed structured examination. The interview covered neurologic, psychiatric, and internal medicine anamnesis, medication past and current, substance abuse, work impairment, detailed sleep-related data, specific sleep medication, and a full-length set of questionnaires including depression, quality of life, sleepiness, anxiety, fatigue, insomnia, and sleep inertia. The data were digitized and imported into statistical software (SPSS by IBM), and dynamic simulation software (Vensim by Ventana Systems Inc.) was used to build a causal loop diagram and stocks and flows diagram as a simulation structure. RESULTS: The overall raw data and simulation-based patterns fit at 76.1%. The simulation results also identified the parameters that contribute the most to patients' subjective experience. These included sleep inertia, the refreshing potential of naps, the quality of nocturnal sleep, and the social aspects of the patient's life. Psychiatric disorders influence the overall pattern at a surprisingly low level. The influence of medication has been studied in detail. Although its contribution to the dynamics looks marginal at first sight, it significantly influences the contribution of other variables to the overall patient experience of the disease. CONCLUSION: Even the simplified dynamic structure designed by the research team reflects the real-life events in patients with IH at the acceptable level of 76.1% and suggests that a similar structure plays an important role in the course of the disease. Therapeutic focus on the parameters identified by the model should enhance the patients' subjective experience throughout illness duration and might even turn the progress from negative into positive. Further research is needed to understand the dynamics of idiopathic hypersomnia in greater detail to better understand the causes and design therapeutic approaches to improve patients' quality of life.

• Keywords
• dynamic modeling, idiopathic hypersomnia, sleep disorders, treatment strategy, work impairment,
• Publication type
• Journal Article MeSH

BACKGROUND AND OBJECTIVES: Recent studies fueled doubts as to whether all currently defined central disorders of hypersomnolence are stable entities, especially narcolepsy type 2 and idiopathic hypersomnia. New reliable biomarkers are needed, and the question arises of whether current diagnostic criteria of hypersomnolence disorders should be reassessed. The main aim of this data-driven observational study was to see whether data-driven algorithms would segregate narcolepsy type 1 and identify more reliable subgrouping of individuals without cataplexy with new clinical biomarkers. METHODS: We used agglomerative hierarchical clustering, an unsupervised machine learning algorithm, to identify distinct hypersomnolence clusters in the large-scale European Narcolepsy Network database. We included 97 variables, covering all aspects of central hypersomnolence disorders such as symptoms, demographics, objective and subjective sleep measures, and laboratory biomarkers. We specifically focused on subgrouping of patients without cataplexy. The number of clusters was chosen to be the minimal number for which patients without cataplexy were put in distinct groups. RESULTS: We included 1,078 unmedicated adolescents and adults. Seven clusters were identified, of which 4 clusters included predominantly individuals with cataplexy. The 2 most distinct clusters consisted of 158 and 157 patients, were dominated by those without cataplexy, and among other variables, significantly differed in presence of sleep drunkenness, subjective difficulty awakening, and weekend-week sleep length difference. Patients formally diagnosed as having narcolepsy type 2 and idiopathic hypersomnia were evenly mixed in these 2 clusters. DISCUSSION: Using a data-driven approach in the largest study on central disorders of hypersomnolence to date, our study identified distinct patient subgroups within the central disorders of hypersomnolence population. Our results contest inclusion of sleep-onset REM periods in diagnostic criteria for people without cataplexy and provide promising new variables for reliable diagnostic categories that better resemble different patient phenotypes. Cluster-guided classification will result in a more solid hypersomnolence classification system that is less vulnerable to instability of single features.

• MeSH
• Idiopathic Hypersomnia * diagnosis   MeSH
• Cataplexy * diagnosis   MeSH
• Humans MeSH
• Adolescent MeSH
• Narcolepsy * diagnosis   drug therapy   MeSH
• Disorders of Excessive Somnolence * diagnosis   epidemiology   MeSH
• Cluster Analysis MeSH
• Check Tag
• Humans MeSH
• Adolescent MeSH
• Publication type
• Journal Article MeSH
• Observational Study MeSH
• Research Support, Non-U.S. Gov't MeSH

Idiopathic hypersomnia was first described in 1976 under two forms: polysymptomatic, characterized by excessive daytime sleepiness, long and unrefreshing naps, nocturnal sleep of abnormally long duration and signs of sleep drunkenness upon awakening; monosymptomatic, manifested by excessive daytime sleepiness only. Yet, after 45 years, this sleep disorder is still poorly delineated and diagnostic criteria produced by successive International Classifications of Sleep Disorders are far from satisfactory. The first part of this review is a historical account of the successive names and descriptions of idiopathic hypersomnia: monosymptomatic and polysymptomatic idiopathic hypersomnia in 1976; central nervous system idiopathic hypersomnia in 1979; idiopathic hypersomnia in 1990; idiopathic hypersomnia with and without long sleep time in 2005; idiopathic hypersomnia again in 2014; and, within the last few years, the proposal of separating idiopathic hypersomnia into a well-defined subtype, idiopathic hypersomnia with long sleep duration, and a more heterogeneous subtype combining idiopathic hypersomnia without long sleep duration and narcolepsy type 2. The second part is a critical review of both current ICSD-3 diagnostic criteria and clinical features, scales and questionnaires, electrophysiological and circadian control tests, research techniques, currently used to diagnose idiopathic hypersomnia. The third part proposes a diagnostic evaluation of idiopathic hypersomnia, in the absence of biologic markers and of robust electrophysiological diagnostic criteria.

• Keywords
• central disorders of hypersomnolence, idiopathic hypersomnia, idiopathic hypersomnia with long sleep duration, idiopathic hypersomnia with long sleep time, idiopathic hypersomnia without long sleep duration, idiopathic hypersomnia without long sleep time, narcolepsy, narcolepsy type 1 and narcolepsy type 2,
• Publication type
• Journal Article MeSH
• Review MeSH