A “HOLTER” for Parkinson's disease: validation of the ability to detect on-off states using the REMPARK system

Altres autors/es

Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica

Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial

Universitat Politècnica de Catalunya. CETpD -Centre d'Estudis Tecnològics per a l'Atenció a la Dependència i la Vida Autònoma

Data de publicació

2018-01-01

Resum

The treatment of Parkinson's disease (PD) with levodopa is very effective. However, over time, motor complications (MCs) appear, restricting the patient from leading a normal life. One of the most disabling MCs is ON-OFF fluctuations. Gathering accurate information about the clinical status of the patient is essential for planning treatment and assessing its effect. Systems such as the REMPARK system, capable of accurately and reliably monitoring ON-OFF fluctuations, are of great interest. Objective To analyze the ability of the REMPARK System to detect ON-OFF fluctuations. Methods Forty-one patients with moderate to severe idiopathic PD were recruited according to the UK Parkinson's Disease Society Brain Bank criteria. Patients with motor fluctuations, freezing of gait and/or dyskinesia and who were able to walk unassisted in the OFF phase, were included in the study. Patients wore the REMPARK System for 3 days and completed a diary of their motor state once every hour. Results The record obtained by the REMPARK System, compared with patient-completed diaries, demonstrated 97% sensitivity in detecting OFF states and 88% specificity (i.e., accuracy in detecting ON states). Conclusion The REMPARK System detects an accurate evaluation of ON-OFF fluctuations in PD; this technology paves the way for an optimisation of the symptomatic control of PD motor symptoms as well as an accurate assessment of medication efficacy.


Peer Reviewed


Postprint (published version)

Tipus de document

Article

Llengua

Anglès

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http://creativecommons.org/licenses/by-nc-nd/3.0/es/

Open Access

Attribution-NonCommercial-NoDerivs 3.0 Spain

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