Journal article
Longitudinal assessment of excessive daytime sleepiness in early Parkinson’s disease
Journal of neurology, neurosurgery and psychiatry, Vol.88(8), pp.653-662
08/2017
DOI: 10.1136/jnnp-2016-315023
PMID: 28554959
Abstract
BackgroundExcessive daytime sleepiness (EDS) is common and disabling in Parkinson’s disease (PD). Predictors of EDS are unclear, and data on biological correlates of EDS in PD are limited. We investigated clinical, imaging and biological variables associated with longitudinal changes in sleepiness in early PD.MethodsThe Parkinson’s Progression Markers Initiative is a prospective cohort study evaluating progression markers in participants with PD who are unmedicated at baseline (n=423) and healthy controls (HC; n=196). EDS was measured with the Epworth Sleepiness Scale (ESS). Clinical, biological and imaging variables were assessed for associations with EDS for up to 3 years. A machine learning approach (random survival forests) was used to investigate baseline predictors of incident EDS.ResultsESS increased in PD from baseline to year 3 (mean±SD 5.8±3.5 to 7.55±4.6, p<0.0001), with no change in HC. Longitudinally, EDS in PD was associated with non-tremor dominant phenotype, autonomic dysfunction, depression, anxiety and probable behaviour disorder, but not cognitive dysfunction or motor severity. Dopaminergic therapy was associated with EDS at years 2 and 3, as dose increased. EDS was also associated with presynaptic dopaminergic dysfunction, whereas biofluid markers at year 1 showed no significant associations with EDS. A predictive index for EDS was generated, which included seven baseline characteristics, including non-motor symptoms and cerebrospinal fluid phosphorylated-tau/total-tau ratio.ConclusionsIn early PD, EDS increases significantly over time and is associated with several clinical variables. The influence of dopaminergic therapy on EDS is dose dependent. Further longitudinal analyses will better characterise associations with imaging and biomarkers.
Details
- Title: Subtitle
- Longitudinal assessment of excessive daytime sleepiness in early Parkinson’s disease
- Creators
- Amy W Amara - Department of Neurology, The University of Alabama at Birmingham, Birmingham, Alabama, USALama M Chahine - Department of Neurology, The University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USAChelsea Caspell-Garcia - Department of Biostatistics, The University of Iowa, Iowa City, Iowa, USAJeffrey D Long - Department of Biostatistics, The University of Iowa, Iowa City, Iowa, USAChristopher Coffey - Department of Biostatistics, The University of Iowa, Iowa City, Iowa, USABirgit Högl - Department of Neurology, Innsbruck Medical University, Innsbruck, AustriaAleksandar Videnovic - Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USAAlex Iranzo - Neurology Service, Hospital Clinic de Barcelona, IDIBAPS, CIBERNED, Barcelona, SpainGeert Mayer - Department of Neurology, Hephata-Klinik, Hephata Hessisches Diakoniezentrum, e.V., Schwalmstadt-Treysa, GermanyNancy Foldvary-Schaefer - Cleveland Clinic Neurological Institute, Cleveland, Ohio, USARon Postuma - Division of Neurology, McGill University, Montreal, Québec, CanadaWolfgang Oertel - Charitable Hertie Foundation, Frankfurt, GermanyShirley Lasch - Institute for Neurodegenerative Disorders, New Haven, Connecticut, USAKen Marek - Institute for Neurodegenerative Disorders, New Haven, Connecticut, USATanya Simuni - Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USAParkinson's Progression Markers
- Resource Type
- Journal article
- Publication Details
- Journal of neurology, neurosurgery and psychiatry, Vol.88(8), pp.653-662
- DOI
- 10.1136/jnnp-2016-315023
- PMID
- 28554959
- NLM abbreviation
- J Neurol Neurosurg Psychiatry
- ISSN
- 0022-3050
- eISSN
- 1468-330X
- Grant note
- DOI: 10.13039/100000864, name: Michael J. Fox Foundation for Parkinson's Research
- Language
- English
- Date published
- 08/2017
- Academic Unit
- Psychiatry; Biostatistics
- Record Identifier
- 9983997446302771
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