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Cox E, Wade R, Hodgson R, Fulbright H, Phung TH, Meader N, Walker S, Rothery C, Simmonds M. Devices for remote continuous monitoring of people with Parkinson's disease: a systematic review and cost-effectiveness analysis. Health Technol Assess 2024; 28:1-187. [PMID: 39021200 PMCID: PMC11331379 DOI: 10.3310/ydsl3294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2024] Open
Abstract
Background Parkinson's disease is a brain condition causing a progressive loss of co ordination and movement problems. Around 145,500 people have Parkinson's disease in the United Kingdom. Levodopa is the most prescribed treatment for managing motor symptoms in the early stages. Patients should be monitored by a specialist every 6-12 months for disease progression and treatment of adverse effects. Wearable devices may provide a novel approach to management by directly monitoring patients for bradykinesia, dyskinesia, tremor and other symptoms. They are intended to be used alongside clinical judgement. Objectives To determine the clinical and cost-effectiveness of five devices for monitoring Parkinson's disease: Personal KinetiGraph, Kinesia 360, KinesiaU, PDMonitor and STAT-ON. Methods We performed systematic reviews of all evidence on the five devices, outcomes included: diagnostic accuracy, impact on decision-making, clinical outcomes, patient and clinician opinions and economic outcomes. We searched MEDLINE and 12 other databases/trial registries to February 2022. Risk of bias was assessed. Narrative synthesis was used to summarise all identified evidence, as the evidence was insufficient for meta-analysis. One included trial provided individual-level data, which was re-analysed. A de novo decision-analytic model was developed to estimate the cost-effectiveness of Personal KinetiGraph and Kinesia 360 compared to standard of care in the UK NHS over a 5-year time horizon. The base-case analysis considered two alternative monitoring strategies: one-time use and routine use of the device. Results Fifty-seven studies of Personal KinetiGraph, 15 of STAT-ON, 3 of Kinesia 360, 1 of KinesiaU and 1 of PDMonitor were included. There was some evidence to suggest that Personal KinetiGraph can accurately measure bradykinesia and dyskinesia, leading to treatment modification in some patients, and a possible improvement in clinical outcomes when measured using the Unified Parkinson's Disease Rating Scale. The evidence for STAT-ON suggested it may be of value for diagnosing symptoms, but there is currently no evidence on its clinical impact. The evidence for Kinesia 360, KinesiaU and PDMonitor is insufficient to draw any conclusions on their value in clinical practice. The base-case results for Personal KinetiGraph compared to standard of care for one-time and routine use resulted in incremental cost-effectiveness ratios of £67,856 and £57,877 per quality-adjusted life-year gained, respectively, with a beneficial impact of the Personal KinetiGraph on Unified Parkinson's Disease Rating Scale domains III and IV. The incremental cost-effectiveness ratio results for Kinesia 360 compared to standard of care for one-time and routine use were £38,828 and £67,203 per quality-adjusted life-year gained, respectively. Limitations The evidence was limited in extent and often low quality. For all devices, except Personal KinetiGraph, there was little to no evidence on the clinical impact of the technology. Conclusions Personal KinetiGraph could reasonably be used in practice to monitor patient symptoms and modify treatment where required. There is too little evidence on STAT-ON, Kinesia 360, KinesiaU or PDMonitor to be confident that they are clinically useful. The cost-effectiveness of remote monitoring appears to be largely unfavourable with incremental cost-effectiveness ratios in excess of £30,000 per quality-adjusted life-year across a range of alternative assumptions. The main driver of cost-effectiveness was the durability of improvements in patient symptoms. Study registration This study is registered as PROSPERO CRD42022308597. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Evidence Synthesis programme (NIHR award ref: NIHR135437) and is published in full in Health Technology Assessment; Vol. 28, No. 30. See the NIHR Funding and Awards website for further award information.
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Affiliation(s)
- Edward Cox
- CHE Technology Assessment Group, University of York, York, UK
| | - Ros Wade
- CRD Technology Assessment Group, University of York, York, UK
| | - Robert Hodgson
- CRD Technology Assessment Group, University of York, York, UK
| | - Helen Fulbright
- CRD Technology Assessment Group, University of York, York, UK
| | - Thai Han Phung
- CHE Technology Assessment Group, University of York, York, UK
| | - Nicholas Meader
- CRD Technology Assessment Group, University of York, York, UK
| | - Simon Walker
- CHE Technology Assessment Group, University of York, York, UK
| | - Claire Rothery
- CHE Technology Assessment Group, University of York, York, UK
| | - Mark Simmonds
- CRD Technology Assessment Group, University of York, York, UK
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Fay-Karmon T, Galor N, Heimler B, Zilka A, Bartsch RP, Plotnik M, Hassin-Baer S. Home-based monitoring of persons with advanced Parkinson's disease using smartwatch-smartphone technology. Sci Rep 2024; 14:9. [PMID: 38167434 PMCID: PMC10761812 DOI: 10.1038/s41598-023-48209-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2023] [Accepted: 11/23/2023] [Indexed: 01/05/2024] Open
Abstract
Movement deterioration is the hallmark of Parkinson's disease (PD), characterized by levodopa-induced motor-fluctuations (i.e., symptoms' variability related to the medication cycle) in advanced stages. However, motor symptoms are typically too sporadically and/or subjectively assessed, ultimately preventing the effective monitoring of their progression, and thus leading to suboptimal treatment/therapeutic choices. Smartwatches (SW) enable a quantitative-oriented approach to motor-symptoms evaluation, namely home-based monitoring (HBM) using an embedded inertial measurement unit. Studies validated such approach against in-clinic evaluations. In this work, we aimed at delineating personalized motor-fluctuations' profiles, thus capturing individual differences. 21 advanced PD patients with motor fluctuations were monitored for 2 weeks using a SW and a smartphone-dedicated app (Intel Pharma Analytics Platform). The SW continuously collected passive data (tremor, dyskinesia, level of activity using dedicated algorithms) and active data, i.e., time-up-and-go, finger tapping, hand tremor and hand rotation carried out daily, once in OFF and once in ON levodopa periods. We observed overall high compliance with the protocol. Furthermore, we observed striking differences among the individual patterns of symptoms' levodopa-related variations across the HBM, allowing to divide our participants among four data-driven, motor-fluctuations' profiles. This highlights the potential of HBM using SW technology for revolutionizing clinical practices.
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Affiliation(s)
- Tsviya Fay-Karmon
- Movement Disorders Institute, Department of Neurology, Sheba Medical Center, Ramat Gan, Israel
| | - Noam Galor
- Center of Advanced Technologies in Rehabilitation, Sheba Medical Center, Ramat Gan, Israel
| | - Benedetta Heimler
- Center of Advanced Technologies in Rehabilitation, Sheba Medical Center, Ramat Gan, Israel
| | - Asaf Zilka
- Movement Disorders Institute, Department of Neurology, Sheba Medical Center, Ramat Gan, Israel
| | - Ronny P Bartsch
- Department of Physics, Bar-Ilan University, Ramat Gan, Israel
| | - Meir Plotnik
- Center of Advanced Technologies in Rehabilitation, Sheba Medical Center, Ramat Gan, Israel
- Department of Physiology and Pharmacology, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Sharon Hassin-Baer
- Movement Disorders Institute, Department of Neurology, Sheba Medical Center, Ramat Gan, Israel.
- Department of Neurology and Neurosurgery, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
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Kehagia AA, Chowienczyk S, Helena van Velthoven M, King E, North T, Shenton D, Abraham J, Langley J, Partridge R, Ankeny U, Gorst T, Edwards E, Whipps S, Batup M, Rideout J, Swabey M, Inches J, Bentley S, Gilbert G, Carroll C. Real-World Evaluation of the Feasibility, Acceptability and Safety of a Remote, Self-Management Parkinson's Disease Care Pathway: A Healthcare Improvement Initiative. JOURNAL OF PARKINSON'S DISEASE 2024; 14:197-208. [PMID: 38250784 PMCID: PMC10836560 DOI: 10.3233/jpd-230205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Indexed: 01/23/2024]
Abstract
BACKGROUND There is significant unmet need for effective and efficiently delivered care for people with Parkinson's disease (PwP). We undertook a service improvement initiative to co-develop and implement a new care pathway, Home Based Care (HBC), based on supported self-management, remote monitoring and the ability to trigger a healthcare contact when needed. OBJECTIVE To evaluate feasibility, acceptability and safety of Home Based Care. METHODS We evaluated data from the first 100 patients on HBC for 6 months. Patient monitoring, performed at baseline and 6-monthly, comprised motor (MDS-UPDRS II and accelerometer), non-motor (NMSQ, PDSS-2, HADS) and quality of life (PDQ) measures. Care quality was audited against Parkinson's UK national audit standards. Process measures captured feasibility. Acceptability was assessed using a mixed-methods approach comprising questionnaires and semi-structured interviews. RESULTS Between October 2019 and January 2021, 108 PwP were enrolled onto HBC, with data from 100 being available at 6 months. Over 90% of all questionnaires were returned, 97% were complete or had < 3 missing items. Reporting and communications occurred within agreed timeframes. Compared with baseline, after 6m on HBC, PD symptoms were stable; more PwP felt listened to (90% vs. 79%) and able to seek help (79% vs. 68%). HBC met 93% of national audit criteria. Key themes from the interviews included autonomy and empowerment. CONCLUSIONS We have demonstrated acceptability, feasibility and safety of our novel remotely delivered Parkinson's care pathway. Ensuring scalability will widen its reach and realize its benefits for underserved communities, enabling formal comparisons with standard care and cost-effectiveness evaluation.
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Affiliation(s)
- Angie A. Kehagia
- School of Biomedical Engineering and Imaging Sciences, King’s Technology Evaluation Centre, King’s College London, UK
- University of Plymouth, Plymouth, UK
| | | | | | - Emma King
- University Hospitals Plymouth NHS Trust, Plymouth, UK
| | | | | | | | | | | | | | - Terry Gorst
- South West Academic Health Science Network, Exeter, UK
| | | | | | | | | | - Mat Swabey
- University Hospitals Plymouth NHS Trust, Plymouth, UK
| | - Jemma Inches
- University Hospitals Plymouth NHS Trust, Plymouth, UK
| | - Sue Bentley
- University Hospitals Plymouth NHS Trust, Plymouth, UK
| | | | - Camille Carroll
- University of Plymouth, Plymouth, UK
- University Hospitals Plymouth NHS Trust, Plymouth, UK
- Newcastle University Translational and Clinical Research Institute, Newcastle, UK
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Moreau C, Rouaud T, Grabli D, Benatru I, Remy P, Marques AR, Drapier S, Mariani LL, Roze E, Devos D, Dupont G, Bereau M, Fabbri M. Overview on wearable sensors for the management of Parkinson's disease. NPJ Parkinsons Dis 2023; 9:153. [PMID: 37919332 PMCID: PMC10622581 DOI: 10.1038/s41531-023-00585-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 10/02/2023] [Indexed: 11/04/2023] Open
Abstract
Parkinson's disease (PD) is affecting about 1.2 million patients in Europe with a prevalence that is expected to have an exponential increment, in the next decades. This epidemiological evolution will be challenged by the low number of neurologists able to deliver expert care for PD. As PD is better recognized, there is an increasing demand from patients for rigorous control of their symptoms and for therapeutic education. In addition, the highly variable nature of symtoms between patients and the fluctuations within the same patient requires innovative tools to help doctors and patients monitor the disease in their usual living environment and adapt treatment in a more relevant way. Nowadays, there are various body-worn sensors (BWS) proposed to monitor parkinsonian clinical features, such as motor fluctuations, dyskinesia, tremor, bradykinesia, freezing of gait (FoG) or gait disturbances. BWS have been used as add-on tool for patients' management or research purpose. Here, we propose a practical anthology, summarizing the characteristics of the most used BWS for PD patients in Europe, focusing on their role as tools to improve treatment management. Consideration regarding the use of technology to monitor non-motor features is also included. BWS obviously offer new opportunities for improving management strategy in PD but their precise scope of use in daily routine care should be clarified.
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Affiliation(s)
- Caroline Moreau
- Department of Neurology, Parkinson's disease expert Center, Lille University, INSERM UMRS_1172, University Hospital Center, Lille, France
- The French Ns-Park Network, Paris, France
| | - Tiphaine Rouaud
- The French Ns-Park Network, Paris, France
- CHU Nantes, Centre Expert Parkinson, Department of Neurology, Nantes, F-44093, France
| | - David Grabli
- The French Ns-Park Network, Paris, France
- Assistance Publique Hôpitaux de Paris, Department of Neurology, CIC Neurosciences, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Sorbonne University, Paris Brain Institute - ICM, Inserm, CNRS, Paris, France
| | - Isabelle Benatru
- The French Ns-Park Network, Paris, France
- Department of Neurology, University Hospital of Poitiers, Poitiers, France
- INSERM, CHU de Poitiers, University of Poitiers, Centre d'Investigation Clinique CIC1402, Poitiers, France
| | - Philippe Remy
- The French Ns-Park Network, Paris, France
- Centre Expert Parkinson, NS-Park/FCRIN Network, CHU Henri Mondor, AP-HP, Equipe NPI, IMRB, INSERM et Faculté de Santé UPE-C, Créteil, FranceService de neurologie, hôpital Henri-Mondor, AP-HP, Créteil, France
| | - Ana-Raquel Marques
- The French Ns-Park Network, Paris, France
- Université Clermont Auvergne, CNRS, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand University Hospital, Neurology department, Clermont-Ferrand, France
| | - Sophie Drapier
- The French Ns-Park Network, Paris, France
- Pontchaillou University Hospital, Department of Neurology, CIC INSERM 1414, Rennes, France
| | - Louise-Laure Mariani
- The French Ns-Park Network, Paris, France
- Assistance Publique Hôpitaux de Paris, Department of Neurology, CIC Neurosciences, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Sorbonne University, Paris Brain Institute - ICM, Inserm, CNRS, Paris, France
| | - Emmanuel Roze
- The French Ns-Park Network, Paris, France
- Assistance Publique Hôpitaux de Paris, Department of Neurology, CIC Neurosciences, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Sorbonne University, Paris Brain Institute - ICM, Inserm, CNRS, Paris, France
| | - David Devos
- The French Ns-Park Network, Paris, France
- Parkinson's Disease Centre of Excellence, Department of Medical Pharmacology, Univ. Lille, INSERM; CHU Lille, U1172 - Degenerative & Vascular Cognitive Disorders, LICEND, NS-Park Network, F-59000, Lille, France
| | - Gwendoline Dupont
- The French Ns-Park Network, Paris, France
- Centre hospitalier universitaire François Mitterrand, Département de Neurologie, Université de Bourgogne, Dijon, France
| | - Matthieu Bereau
- The French Ns-Park Network, Paris, France
- Service de neurologie, université de Franche-Comté, CHRU de Besançon, 25030, Besançon, France
| | - Margherita Fabbri
- The French Ns-Park Network, Paris, France.
- Department of Neurosciences, Clinical Investigation Center CIC 1436, Parkinson Toulouse Expert Centre, NS-Park/FCRIN Network and NeuroToul COEN Center, Toulouse University Hospital, INSERM, University of Toulouse 3, Toulouse, France.
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Geraedts VJ, van Vugt JPP, Marinus J, Kuiper R, Middelkoop HAM, Zutt R, van der Gaag NA, Hoffmann CFE, Dorresteijn LDA, van Hilten JJ, Contarino MF. Predicting Motor Outcome and Quality of Life After Subthalamic Deep Brain Stimulation for Parkinson's Disease: The Role of Standard Screening Measures and Wearable-Data. JOURNAL OF PARKINSON'S DISEASE 2023:JPD225101. [PMID: 37182900 DOI: 10.3233/jpd-225101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
BACKGROUND Standardized screening for subthalamic deep brain stimulation (STN DBS) in Parkinson's disease (PD) patients is crucial to determine eligibility, but its utility to predict postoperative outcomes in eligible patients is inconclusive. It is unknown whether wearable data can contribute to this aim. OBJECTIVE To evaluate the utility of universal components incorporated in the DBS screening, complemented by a wearable sensor, to predict motor outcomes and Quality of life (QoL) one year after STN DBS surgery. METHODS Consecutive patients were included in the OPTIMIST cohort study from two DBS centers. Standardized assessments included a preoperative Levodopa Challenge Test (LCT), and questionnaires on QoL and non-motor symptoms including cognition, psychiatric symptoms, impulsiveness, autonomic symptoms, and sleeping problems. Moreover, an ambulatory wearable sensor (Parkinson Kinetigraph (PKG)) was used. Postoperative assessments were similar and also included a Stimulation Challenge Test to determine DBS effects on motor function. RESULTS Eighty-three patients were included (median (interquartile range) age 63 (56-68) years, 36% female). Med-OFF (Stim-OFF) motor severity deteriorated indicating disease progression, but patients significantly improved in terms of Med-ON (Stim-ON) motor function, motor fluctuations, QoL, and most non-motor domains. Motor outcomes were not predicted by preoperative tests, including covariates of either LCT or PKG. Postoperative QoL was predicted by better preoperative QoL, lower age, and more preoperative impulsiveness scores in multivariate models. CONCLUSION Data from the DBS screening including wearable data do not predict postoperative motor outcome at one year. Post-DBS QoL appears primarily driven by non-motor symptoms, rather than by motor improvement.
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Affiliation(s)
- Victor J Geraedts
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | | | - Johan Marinus
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
| | - Roy Kuiper
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Neurology, HAGA Teaching Hospital, Den Haag, the Netherlands
| | - Huub A M Middelkoop
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
| | - Rodi Zutt
- Department of Neurology, HAGA Teaching Hospital, Den Haag, the Netherlands
| | - Niels A van der Gaag
- Department of Neurosurgery, HAGA Teaching Hospital, Den Haag, the Netherlands
- Department of Neurosurgery, Leiden University Medical Center, Leiden, the Netherlands
| | - Carel F E Hoffmann
- Department of Neurosurgery, HAGA Teaching Hospital, Den Haag, the Netherlands
| | | | - Jacobus J van Hilten
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
| | - Maria Fiorella Contarino
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Neurology, HAGA Teaching Hospital, Den Haag, the Netherlands
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