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Title: Correlation of Quantitative Motor State Assessment Using a Kinetograph and Patient Diaries in Advanced PD: Data from an Observational Study.
Austin Authors: Ossig, Christiana;Gandor, Florin;Fauser, Mareike;Bosredon, Cecile;Churilov, Leonid ;Reichmann, Heinz;Horne, Malcolm K;Ebersbach, Georg;Storch, Alexander
Affiliation: Division of Neurodegenerative Diseases, Department of Neurology, Technische Universität Dresden, Dresden, Germany
Movement Disorders Clinic, Beelitz-Heilstätten, Germany
German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Heidelberg, Victoria, Australia
RMIT University, Melbourne, Australia
Department of Neurology, Technische Universität Dresden, D-01307, Dresden, Germany
Florey Institute for Neuroscience and Mental Health, University of Melbourne, Parkville, Australia
St Vincent's Hospital, Fitzroy, Victoria, 3065, Australia
Department of Neurology, University of Rostock, Rostock, Germany
Issue Date: 2016 2016-08-24
Publication information: PLoS One 2016; 11(8): e0161559
Abstract: Effective management and development of new treatment strategies for response fluctuations in advanced Parkinson's disease (PD) largely depends on clinical rating instruments such as the PD home diary. The Parkinson's kinetigraph (PKG) measures movement accelerations and analyzes the spectral power of the low frequencies of the accelerometer data. New algorithms convert each hour of continuous PKG data into one of the three motor categories used in the PD home diary, namely motor Off state and On state with and without dyskinesia. To compare quantitative motor state assessment in fluctuating PD patients using the PKG with motor state ratings from PD home diaries. Observational cohort study on 24 in-patients with documented motor fluctuations who completed diaries by rating motor Off, On without dyskinesia, On with dyskinesia, and asleep for every hour for 5 consecutive days. Simultaneously collected PKG data (recorded between 6 am and 10 pm) were analyzed and calibrated to the patient's individual thresholds for Off and dyskinetic state by novel algorithms classifying the continuous accelerometer data into these motor states for every hour between 6 am and 10 pm. From a total of 2,040 hours, 1,752 hours (87.4%) were available for analyses from calibrated PKG data (7.5% sleeping time and 5.1% unclassified motor state time were excluded from analyses). Distributions of total motor state hours per day measured by PKG showed moderate-to-strong correlation to those assessed by diaries for the different motor states (Pearson's correlations coefficients: 0.404-0.658), but inter-rating method agreements on the single-hour-level were only low-to-moderate (Cohen's κ: 0.215-0.324). The PKG has been shown to capture motor fluctuations in patients with advanced PD. The limited correlation of hour-to-hour diary and PKG recordings should be addressed in further studies.
DOI: 10.1371/journal.pone.0161559
ORCID: 0000-0002-9807-6606
PubMed URL: 27556806
Type: Journal Article
Appears in Collections:Journal articles

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