Literature DB >> 28963889

A "HOLTER" for Parkinson's disease: Validation of the ability to detect on-off states using the REMPARK system.

Àngels Bayés1, Albert Samá2, Anna Prats3, Carlos Pérez-López2, Maricruz Crespo-Maraver4, Juan Manuel Moreno2, Sheila Alcaine5, Alejandro Rodriguez-Molinero6, Berta Mestre5, Paola Quispe5, Ana Correia de Barros7, Rui Castro7, Alberto Costa8, Roberta Annicchiarico9, Patrick Browne10, Tim Counihan3, Hadas Lewy11, Gabriel Vainstein11, Leo R Quinlan12, Dean Sweeney13, Gearóid ÓLaighin12, Jordi Rovira14, Daniel Rodrigue Z-Martin2, Joan Cabestany2.   

Abstract

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 3days 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.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Automatic assessment; Motor complications; On-off fluctuations; Parkinson’s disease; REMPARK system; Wearable sensor

Mesh:

Year:  2017        PMID: 28963889     DOI: 10.1016/j.gaitpost.2017.09.031

Source DB:  PubMed          Journal:  Gait Posture        ISSN: 0966-6362            Impact factor:   2.840


  12 in total

Review 1.  Point of view: Wearable systems for at-home monitoring of motor complications in Parkinson's disease should deliver clinically actionable information.

Authors:  Behnaz Ghoraani; James E Galvin; Joohi Jimenez-Shahed
Journal:  Parkinsonism Relat Disord       Date:  2021-01-30       Impact factor: 4.891

2.  Feasibility and Utility of mHealth for the Remote Monitoring of Parkinson Disease: Ancillary Study of the PD_manager Randomized Controlled Trial.

Authors:  Dimitris Gatsios; Angelo Antonini; Giovanni Gentile; Andrea Marcante; Clelia Pellicano; Lucia Macchiusi; Francesca Assogna; Gianfranco Spalletta; Heather Gage; Morro Touray; Lada Timotijevic; Charo Hodgkins; Maria Chondrogiorgi; George Rigas; Dimitrios I Fotiadis; Spyridon Konitsiotis
Journal:  JMIR Mhealth Uhealth       Date:  2020-06-29       Impact factor: 4.773

Review 3.  Gait Analysis in Parkinson's Disease: An Overview of the Most Accurate Markers for Diagnosis and Symptoms Monitoring.

Authors:  Lazzaro di Biase; Alessandro Di Santo; Maria Letizia Caminiti; Alfredo De Liso; Syed Ahmar Shah; Lorenzo Ricci; Vincenzo Di Lazzaro
Journal:  Sensors (Basel)       Date:  2020-06-22       Impact factor: 3.576

4.  Systematic Review Looking at the Use of Technology to Measure Free-Living Symptom and Activity Outcomes in Parkinson's Disease in the Home or a Home-like Environment.

Authors:  Catherine Morgan; Michal Rolinski; Roisin McNaney; Bennet Jones; Lynn Rochester; Walter Maetzler; Ian Craddock; Alan L Whone
Journal:  J Parkinsons Dis       Date:  2020       Impact factor: 5.568

5.  Feasibility of a continuous, multi-sensor remote health monitoring approach in persons living with neurodegenerative disease.

Authors:  F Elizabeth Godkin; Erin Turner; Youness Demnati; Adam Vert; Angela Roberts; Richard H Swartz; Paula M McLaughlin; Kyle S Weber; Vanessa Thai; Kit B Beyer; Benjamin Cornish; Agessandro Abrahao; Sandra E Black; Mario Masellis; Lorne Zinman; Derek Beaton; Malcolm A Binns; Vivian Chau; Donna Kwan; Andrew Lim; Douglas P Munoz; Stephen C Strother; Kelly M Sunderland; Brian Tan; William E McIlroy; Karen Van Ooteghem
Journal:  J Neurol       Date:  2021-10-27       Impact factor: 6.682

6.  Body-Worn Sensors for Parkinson's disease: A qualitative approach with patients and healthcare professionals.

Authors:  Clara Virbel-Fleischman; Yann Rétory; Sébastien Hardy; Camille Huiban; Jean-Christophe Corvol; David Grabli
Journal:  PLoS One       Date:  2022-05-05       Impact factor: 3.240

Review 7.  An update on adaptive deep brain stimulation in Parkinson's disease.

Authors:  Jeroen G V Habets; Margot Heijmans; Mark L Kuijf; Marcus L F Janssen; Yasin Temel; Pieter L Kubben
Journal:  Mov Disord       Date:  2018-10-24       Impact factor: 10.338

8.  Monitoring Parkinson's disease symptoms during daily life: a feasibility study.

Authors:  Margot Heijmans; Jeroen G V Habets; Christian Herff; Jos Aarts; An Stevens; Mark L Kuijf; Pieter L Kubben
Journal:  NPJ Parkinsons Dis       Date:  2019-09-30

9.  Predictive Value of Ambulatory Objective Movement Measurement for Outcomes of Levodopa/Carbidopa Intestinal Gel Infusion.

Authors:  Gökçe Kilinçalp; Anne-Christine Sjöström; Barbro Eriksson; Björn Holmberg; Radu Constantinescu; Filip Bergquist
Journal:  J Pers Med       Date:  2022-01-02

Review 10.  A Long Way to Go: Patient Perspectives on Digital Health for Parkinson's Disease.

Authors:  Sara Riggare; Jon Stamford; Maria Hägglund
Journal:  J Parkinsons Dis       Date:  2021       Impact factor: 5.568

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