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From the Sleep Wake Center SEIN Heemstede (J.K.G., R.F., G.J.L.), Stichting Epilepsie Instellingen Nederland, Heemstede; Department of Neurology and Clinical Neurophysiology (J.K.G., R.F., G.J.L.), Leiden University Medical Center; Department of Anatomy and Neurosciences (J.K.G., S.M.), Amsterdam UMC (Location VUmc), the Netherlands; Center for Sleep Medicine, Sleep Research and Epileptology (Z.Z., R.K.), Klinik Barmelweid AG, Barmelweid, Switzerland; Leiden Observatory (M.S.S.L.O.), Leiden University, the Netherlands; Sleep-Wake Disorders Unit (Y.D., L.B.), Department of Neurology, Gui-de-Chauliac Hospital, CHU Montpellier; National Reference Centre for Orphan Diseases, Narcolepsy, Idiopathic Hypersomnia, and Kleine-Levin Syndrome (Y.D., L.B.); Institute for Neurosciences of Montpellier INM (Y.D., L.B.), Univ Montpellier, INSERM, France; Neurology Department (G.M.), Hephata Klinik, Schwalmstadt, Germany; Department of Biomedical, Metabolic and Neural Sciences (G.P.), University of Modena and Reggio Emilia; IRCCS Istituto delle Scienze Neurologiche di Bologna (G.P, F.P.), Bologna, Italy; Neurophysiology and Sleep Disorders Unit (R.d.R.-V.), Hospital Vithas Nuestra Señora de América, Madrid; Neurology Service (J.S.C.), Institut de Neurociències Hospital Clínic, University of Barcelona, Spain; Neurology Department and Centre of Clinical Neurosciences (K.S.), First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic; Helsinki Sleep Clinic (M.P.), Vitalmed Research Center, Finland; Sleep Medicine Center Kempenhaeghe (S.O.), Heeze; Eindhoven University of Technology (S.O.), the Netherlands; Sleep and Epilepsy Unit-Clinical Neurophysiology Service (R.P.-A.), University General Hospital Gregorio Marañón, Research Institute Gregorio Marañón; University Complutense of Madrid (R.P.-A.), Spain; Center for Investigation and Research in Sleep (R.H.), Lausanne University Hospital, Switzerland; Serviço de Neurofisiologia (A.M.d.S.), Hospital Santo António/Centro Hospitalar Universitário do Porto and UMIB-Instituto Ciências Biomédicas Abel Salazar, Universidade do Porto, Portugal; Neurology Department (B.H., A.H.), Sleep Disorders Clinic, Innsbruck Medical University, Austria; Department of Clinical Neurophysiology (A.W.), Institute of Psychiatry and Neurology, Warsaw, Poland; Department of Sleep Medicine and Neuromuscular Disorders (A.H.), University of Münster, Germany; Neurology Department (E.F.), Medical Faculty of P.J. Safarik University, University Hospital of L. Pasteur Kosice, Kosice, Slovak Republic; Neurology Department (M.M.), EOC, Ospedale Regionale di Lugano, Ticino, Switzerland; Department of Sleep Medicine (J.B.), National Institute of Mental Health, Klecany, Czech Republic; Fundacio d`Investigacio Sanitaria de les illes balears (F.C.), Hospital Universitari Son Espases, Palma de Mallorca, Spain; Department of Neurology (C.L.B., M.H.S., R.K.), Inselspital, Bern University Hospital, University of Bern, Switzerland; and Department of Biomedical and Neuromotor Sciences (F.P.), University of Bologna, Italy.
Published: June 2022
AI Article Synopsis
Article Abstract
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.
