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Pfledderer CD, von Klinggraeff L, Burkart S, da Silva Bandeira A, Lubans DR, Jago R, Okely AD, van Sluijs EMF, Ioannidis JPA, Thrasher JF, Li X, Beets MW. Consolidated guidance for behavioral intervention pilot and feasibility studies. Pilot Feasibility Stud 2024; 10:57. [PMID: 38582840 PMCID: PMC10998328 DOI: 10.1186/s40814-024-01485-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 03/26/2024] [Indexed: 04/08/2024] Open
Abstract
BACKGROUND In the behavioral sciences, conducting pilot and/or feasibility studies (PFS) is a key step that provides essential information used to inform the design, conduct, and implementation of a larger-scale trial. There are more than 160 published guidelines, reporting checklists, frameworks, and recommendations related to PFS. All of these publications offer some form of guidance on PFS, but many focus on one or a few topics. This makes it difficult for researchers wanting to gain a broader understanding of all the relevant and important aspects of PFS and requires them to seek out multiple sources of information, which increases the risk of missing key considerations to incorporate into their PFS. The purpose of this study was to develop a consolidated set of considerations for the design, conduct, implementation, and reporting of PFS for interventions conducted in the behavioral sciences. METHODS To develop this consolidation, we undertook a review of the published guidance on PFS in combination with expert consensus (via a Delphi study) from the authors who wrote such guidance to inform the identified considerations. A total of 161 PFS-related guidelines, checklists, frameworks, and recommendations were identified via a review of recently published behavioral intervention PFS and backward/forward citation tracking of a well-known PFS literature (e.g., CONSORT Ext. for PFS). Authors of all 161 PFS publications were invited to complete a three-round Delphi survey, which was used to guide the creation of a consolidated list of considerations to guide the design, conduct, and reporting of PFS conducted by researchers in the behavioral sciences. RESULTS A total of 496 authors were invited to take part in the three-round Delphi survey (round 1, N = 46; round 2, N = 24; round 3, N = 22). A set of twenty considerations, broadly categorized into six themes (intervention design, study design, conduct of trial, implementation of intervention, statistical analysis, and reporting) were generated from a review of the 161 PFS-related publications as well as a synthesis of feedback from the three-round Delphi process. These 20 considerations are presented alongside a supporting narrative for each consideration as well as a crosswalk of all 161 publications aligned with each consideration for further reading. CONCLUSION We leveraged expert opinion from researchers who have published PFS-related guidelines, checklists, frameworks, and recommendations on a wide range of topics and distilled this knowledge into a valuable and universal resource for researchers conducting PFS. Researchers may use these considerations alongside the previously published literature to guide decisions about all aspects of PFS, with the hope of creating and disseminating interventions with broad public health impact.
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Affiliation(s)
- Christopher D Pfledderer
- Department of Health Promotion and Behavioral Sciences, The University of Texas Health Science Center at Houston, School of Public Health in Austin, Austin, TX, 78701, USA.
- Michael and Susan Dell Center for Healthy Living, The University of Texas Health Science Center at Houston, School of Public Health in Austin, Austin, TX, 78701, USA.
| | | | - Sarah Burkart
- Arnold School of Public Health, University of South Carolina, Columbia, SC, 29205, USA
| | | | - David R Lubans
- College of Human and Social Futures, The University of Newcastle Australia, Callaghan, NSW, 2308, Australia
| | - Russell Jago
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, BS8 1QU, UK
| | - Anthony D Okely
- Faculty of Arts, Social Sciences and Humanities, School of Health and Society, University of Wollongong, Wollongong, NSW, 2522, Australia
| | | | - John P A Ioannidis
- Department of Medicine, Stanford University, Stanford, CA, USA
- Department of Epidemiology and Population Health, Stanford University, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
- Department of Statistics, Stanford University, Stanford, CA, USA
- Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA
| | - James F Thrasher
- Arnold School of Public Health, University of South Carolina, Columbia, SC, 29205, USA
| | - Xiaoming Li
- Arnold School of Public Health, University of South Carolina, Columbia, SC, 29205, USA
| | - Michael W Beets
- Arnold School of Public Health, University of South Carolina, Columbia, SC, 29205, USA
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Pfledderer CD, von Klinggraeff L, Burkart S, da Silva Bandeira A, Lubans DR, Jago R, Okely AD, van Sluijs EM, Ioannidis JP, Thrasher JF, Li X, Beets MW. Expert Perspectives on Pilot and Feasibility Studies: A Delphi Study and Consolidation of Considerations for Behavioral Interventions. RESEARCH SQUARE 2023:rs.3.rs-3370077. [PMID: 38168263 PMCID: PMC10760234 DOI: 10.21203/rs.3.rs-3370077/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Background In the behavioral sciences, conducting pilot and/or feasibility studies (PFS) is a key step that provides essential information used to inform the design, conduct, and implementation of a larger-scale trial. There are more than 160 published guidelines, reporting checklists, frameworks, and recommendations related to PFS. All of these publications offer some form of guidance on PFS, but many focus on one or a few topics. This makes it difficult for researchers wanting to gain a broader understanding of all the relevant and important aspects of PFS and requires them to seek out multiple sources of information, which increases the risk of missing key considerations to incorporate into their PFS. The purpose of this study was to develop a consolidated set of considerations for the design, conduct, implementation, and reporting of PFS for interventions conducted in the behavioral sciences. Methods To develop this consolidation, we undertook a review of the published guidance on PFS in combination with expert consensus (via a Delphi study) from the authors who wrote such guidance to inform the identified considerations. A total of 161 PFS-related guidelines, checklists, frameworks, and recommendations were identified via a review of recently published behavioral intervention PFS and backward/forward citation tracking of well-know PFS literature (e.g., CONSORT Ext. for PFS). Authors of all 161 PFS publications were invited to complete a three-round Delphi survey, which was used to guide the creation of a consolidated list of considerations to guide the design, conduct, and reporting of PFS conducted by researchers in the behavioral sciences. Results A total of 496 authors were invited to take part in the Delphi survey, 50 (10.1%) of which completed all three rounds, representing 60 (37.3%) of the 161 identified PFS-related guidelines, checklists, frameworks, and recommendations. A set of twenty considerations, broadly categorized into six themes (Intervention Design, Study Design, Conduct of Trial, Implementation of Intervention, Statistical Analysis and Reporting) were generated from a review of the 161 PFS-related publications as well as a synthesis of feedback from the three-round Delphi process. These 20 considerations are presented alongside a supporting narrative for each consideration as well as a crosswalk of all 161 publications aligned with each consideration for further reading. Conclusion We leveraged expert opinion from researchers who have published PFS-related guidelines, checklists, frameworks, and recommendations on a wide range of topics and distilled this knowledge into a valuable and universal resource for researchers conducting PFS. Researchers may use these considerations alongside the previously published literature to guide decisions about all aspects of PFS, with the hope of creating and disseminating interventions with broad public health impact.
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Affiliation(s)
| | | | - Sarah Burkart
- University of South Carolina Arnold School of Public Health
| | | | | | - Russ Jago
- University of Bristol Population Health Sciences
| | | | | | | | | | - Xiaoming Li
- University of South Carolina Arnold School of Public Health
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Sorici A, Băjenaru L, Mocanu IG, Florea AM, Tsakanikas P, Ribigan AC, Pedullà L, Bougea A. Monitoring and Predicting Health Status in Neurological Patients: The ALAMEDA Data Collection Protocol. Healthcare (Basel) 2023; 11:2656. [PMID: 37830693 PMCID: PMC10572511 DOI: 10.3390/healthcare11192656] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 09/12/2023] [Accepted: 09/22/2023] [Indexed: 10/14/2023] Open
Abstract
(1) Objective: We explore the predictive power of a novel stream of patient data, combining wearable devices and patient reported outcomes (PROs), using an AI-first approach to classify the health status of Parkinson's disease (PD), multiple sclerosis (MS) and stroke patients (collectively named PMSS). (2) Background: Recent studies acknowledge the burden of neurological disorders on patients and on the healthcare systems managing them. To address this, effort is invested in the digital transformation of health provisioning for PMSS patients. (3) Methods: We introduce the data collection journey within the ALAMEDA project, which continuously collects PRO data for a year through mobile applications and supplements them with data from minimally intrusive wearable devices (accelerometer bracelet, IMU sensor belt, ground force measuring insoles, and sleep mattress) worn for 1-2 weeks at each milestone. We present the data collection schedule and its feasibility, the mapping of medical predictor variables to wearable device capabilities and mobile application functionality. (4) Results: A novel combination of wearable devices and smartphone applications required for the desired analysis of motor, sleep, emotional and quality-of-life outcomes is introduced. AI-first analysis methods are presented that aim to uncover the prediction capability of diverse longitudinal and cross-sectional setups (in terms of standard medical test targets). Mobile application development and usage schedule facilitates the retention of patient engagement and compliance with the study protocol.
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Affiliation(s)
- Alexandru Sorici
- AI-MAS Laboratory, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania; (L.B.); (I.G.M.); (A.M.F.)
| | - Lidia Băjenaru
- AI-MAS Laboratory, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania; (L.B.); (I.G.M.); (A.M.F.)
| | - Irina Georgiana Mocanu
- AI-MAS Laboratory, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania; (L.B.); (I.G.M.); (A.M.F.)
| | - Adina Magda Florea
- AI-MAS Laboratory, National University of Science and Technology Politehnica Bucharest, 060042 Bucharest, Romania; (L.B.); (I.G.M.); (A.M.F.)
| | - Panagiotis Tsakanikas
- Institute of Communication and Computer Systems, National Technical University of Athens, 10682 Athens, Greece;
| | - Athena Cristina Ribigan
- Department of Neurology, University Emergency Hospital Bucharest, 050098 Bucharest, Romania;
- Department of Neurology, Faculty of Medicine, University of Medicine and Pharmacy “Carol Davila”, 050474 Bucharest, Romania
| | - Ludovico Pedullà
- Scientific Research Area, Italian Multiple Sclerosis Foundation, 16149 Genoa, Italy;
| | - Anastasia Bougea
- 1st Department of Neurology, Eginition Hospital, National and Kapodistrian University of Athens, 11528 Athens, Greece;
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Antonini A, Reichmann H, Gentile G, Garon M, Tedesco C, Frank A, Falkenburger B, Konitsiotis S, Tsamis K, Rigas G, Kostikis N, Ntanis A, Pattichis C. Toward objective monitoring of Parkinson's disease motor symptoms using a wearable device: wearability and performance evaluation of PDMonitor ®. Front Neurol 2023; 14:1080752. [PMID: 37260606 PMCID: PMC10228366 DOI: 10.3389/fneur.2023.1080752] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 02/27/2023] [Indexed: 06/02/2023] Open
Abstract
Parkinson's disease (PD) is characterized by a variety of motor and non-motor symptoms. As disease progresses, fluctuations in the response to levodopa treatment may develop, along with emergence of freezing of gait (FoG) and levodopa induced dyskinesia (LiD). The optimal management of the motor symptoms and their complications, depends, principally, on the consistent detection of their course, leading to improved treatment decisions. During the last few years, wearable devices have started to be used in the clinical practice for monitoring patients' PD-related motor symptoms, during their daily activities. This work describes the results of 2 multi-site clinical studies (PDNST001 and PDNST002) designed to validate the performance and the wearability of a new wearable monitoring device, the PDMonitor®, in the detection of PD-related motor symptoms. For the studies, 65 patients with Parkinson's disease and 28 healthy individuals (controls) were recruited. Specifically, during the Phase I of the first study, participants used the monitoring device for 2-6 h in a clinic while neurologists assessed the exhibited parkinsonian symptoms every half hour using the Unified Parkinson's Disease Rating Scale (UPDRS) Part III, as well as the Abnormal Involuntary Movement Scale (AIMS) for dyskinesia severity assessment. The goal of Phase I was data gathering. On the other hand, during the Phase II of the first study, as well as during the second study (PDNST002), day-to-day variability was evaluated, with patients in the former and with control subjects in the latter. In both cases, the device was used for a number of days, with the subjects being unsupervised and free to perform any kind of daily activities. The monitoring device produced estimations of the severity of the majority of PD-related motor symptoms and their fluctuations. Statistical analysis demonstrated that the accuracy in the detection of symptoms and the correlation between their severity and the expert evaluations were high. As a result, the studies confirmed the effectiveness of the system as a continuous telemonitoring solution, easy to be used to facilitate decision-making for the treatment of patients with Parkinson's disease.
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Affiliation(s)
- Angelo Antonini
- Parkinson and Movement Disorders Unit, Study Center for Neurodegeneration (CESNE), Department of Neuroscience, University of Padua, Padua, Italy
| | - Heinz Reichmann
- Department of Neurology, University Hospital Carl Gustav Carus and Carl Gustav Carus Faculty of Medicine, Technische Universitat Dresden, Dresden, Germany
| | - Giovanni Gentile
- Parkinson and Movement Disorders Unit, Study Center for Neurodegeneration (CESNE), Department of Neuroscience, University of Padua, Padua, Italy
| | - Michela Garon
- Parkinson and Movement Disorders Unit, Study Center for Neurodegeneration (CESNE), Department of Neuroscience, University of Padua, Padua, Italy
| | - Chiara Tedesco
- Parkinson and Movement Disorders Unit, Study Center for Neurodegeneration (CESNE), Department of Neuroscience, University of Padua, Padua, Italy
| | - Anika Frank
- Department of Neurology, University Hospital Carl Gustav Carus and Carl Gustav Carus Faculty of Medicine, Technische Universitat Dresden, Dresden, Germany
- German Center for Neurodegenerative Diseases (DZNE), Dresden, Germany
| | - Bjoern Falkenburger
- Department of Neurology, University Hospital Carl Gustav Carus and Carl Gustav Carus Faculty of Medicine, Technische Universitat Dresden, Dresden, Germany
- German Center for Neurodegenerative Diseases (DZNE), Dresden, Germany
| | - Spyridon Konitsiotis
- Department of Neurology, University Hospital of Ioannina and Faculty of Medicine, School of Health Sciences, University of Ioannina, Ioannina, Greece
| | - Konstantinos Tsamis
- Department of Neurology, University Hospital of Ioannina and Faculty of Medicine, School of Health Sciences, University of Ioannina, Ioannina, Greece
| | | | | | | | - Constantinos Pattichis
- Department of Computer Science and Biomedical Engineering Research Centre, University of Cyprus, Nicosia, Cyprus
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Aboye GT, Vande Walle M, Simegn GL, Aerts JM. mHealth in sub-Saharan Africa and Europe: A systematic review comparing the use and availability of mHealth approaches in sub-Saharan Africa and Europe. Digit Health 2023; 9:20552076231180972. [PMID: 37377558 PMCID: PMC10291558 DOI: 10.1177/20552076231180972] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 05/23/2023] [Indexed: 06/29/2023] Open
Abstract
Background mHealth can help with healthcare service delivery for various health issues, but there's a significant gap in the availability and use of mHealth systems between sub-Saharan Africa and Europe, despite the ongoing digitalization of the global healthcare system. Objective This work aims to compare and investigate the use and availability of mHealth systems in sub-Saharan Africa and Europe, and identify gaps in current mHealth development and implementation in both regions. Methods The study adhered to the PRISMA 2020 guidelines for article search and selection to ensure an unbiased comparison between sub-Saharan Africa and Europe. Four databases (Scopus, Web of Science, IEEE Xplore, and PubMed) were used, and articles were evaluated based on predetermined criteria. Details on the mHealth system type, goal, patient type, health concern, and development stage were collected and recorded in a Microsoft Excel worksheet. Results The search query produced 1020 articles for sub-Saharan Africa and 2477 articles for Europe. After screening for eligibility, 86 articles for sub-Saharan Africa and 297 articles for Europe were included. To minimize bias, two reviewers conducted the article screening and data retrieval. Sub-Saharan Africa used SMS and call-based mHealth methods for consultation and diagnosis, mainly for young patients such as children and mothers, and for issues such as HIV, pregnancy, childbirth, and child care. Europe relied more on apps, sensors, and wearables for monitoring, with the elderly as the most common patient group, and the most common health issues being cardiovascular disease and heart failure. Conclusion Wearable technology and external sensors are heavily used in Europe, whereas they are seldom used in sub-Saharan Africa. More efforts should be made to use the mHealth system to improve health outcomes in both regions, incorporating more cutting-edge technologies like wearables internal and external sensors. Undertaking context-based studies, identifying determinants of mHealth systems use, and considering these determinants during mHealth system design could enhance mHealth availability and utilization.
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Affiliation(s)
- Genet Tadese Aboye
- M3-BIORES (Measure, Model & Manage Bioreponses), Division of Animal and Human Health Engineering, Department of Biosystems, KU Leuven, Leuven, Belgium
- School of Biomedical Engineering, Jimma University, Jimma, Ethiopia
| | - Martijn Vande Walle
- M3-BIORES (Measure, Model & Manage Bioreponses), Division of Animal and Human Health Engineering, Department of Biosystems, KU Leuven, Leuven, Belgium
| | | | - Jean-Marie Aerts
- M3-BIORES (Measure, Model & Manage Bioreponses), Division of Animal and Human Health Engineering, Department of Biosystems, KU Leuven, Leuven, Belgium
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Personalized Care in Late-Stage Parkinson’s Disease: Challenges and Opportunities. J Pers Med 2022; 12:jpm12050813. [PMID: 35629235 PMCID: PMC9147917 DOI: 10.3390/jpm12050813] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 05/10/2022] [Accepted: 05/17/2022] [Indexed: 12/11/2022] Open
Abstract
Late-stage Parkinson’s disease (LSPD) patients are highly dependent on activities of daily living and require significant medical needs. In LSPD, there is a significant caregiver burden and greater health economic impact compared to earlier PD stages. The clinical presentation in LSPD is dominated by motor and non-motor symptoms (NMS) that most of the time have a sub-optimal to no response to dopaminergic treatment, especially when dementia is present. Non-pharmacological interventions, including physiotherapy, cognitive stimulation, speech, occupational therapy, and a specialized PD nurse, assume a key role in LSPD to mitigate the impact of disease milestones or prevent acute clinical worsening and optimize the management of troublesome NMS. However, the feasibility of these approaches is limited by patients’ cognitive impairment and the difficulty in delivering care at home. The present care challenge for LSPD is the ability to offer a person-centered, home-delivered palliative care model based on Advanced Care Planning. An ongoing European multicentric project, PD_Pal, aims to address this challenge.
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Vellata C, Belli S, Balsamo F, Giordano A, Colombo R, Maggioni G. Effectiveness of Telerehabilitation on Motor Impairments, Non-motor Symptoms and Compliance in Patients With Parkinson's Disease: A Systematic Review. Front Neurol 2021; 12:627999. [PMID: 34512495 PMCID: PMC8427282 DOI: 10.3389/fneur.2021.627999] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Accepted: 07/19/2021] [Indexed: 12/17/2022] Open
Abstract
Introduction: Parkinson's disease (PD) is a chronic neurodegenerative disease involving a progressive alteration of the motor and non-motor function. PD influences the patient's daily living and reduces participation and quality of life in all phases of the disease. Early physical exercise can mitigate the effects of symptoms but access to specialist care is difficult. With current technological progress, telemedicine, and telerehabilitation is now a viable option for managing patients, although few studies have investigated the use of telerehabilitation in PD. In this systematic review, was investigated whether telerehabilitation leads to improvements in global or specific motor tasks (gait and balance, hand function) and non-motor dysfunction (motor speech disorder, dysphagia). The impact of TR on quality of life and patient satisfaction, were also assessed. The usage of telerehabilitation technologies in the management of cognitive impairment was not addressed. Method: An electronic database search was performed using the following databases: PubMed/MEDLINE, COCHRANE Library, PEDro, and SCOPUS for data published between January 2005 and December 2019 on the effects of telerehabilitation systems in managing motor and non-motor symptoms. This systematic review was conducted in accordance with the PRISMA guideline and was registered in the PROSPERO database (CRD42020141300). Results: A total of 15 articles involving 421 patients affected by PD were analyzed. The articles were divided into two categories based on their topic of interest or outcome. The first category consisted of the effects of telerehabilitation on gait and balance (3), dexterity of the upper limbs (3), and bradykinesia (0); the second category regarded non-motor symptoms such as speech disorders (8) and dysphagia (0). Quality of life (7) and patient satisfaction (8) following telerehabilitation programs were also analyzed, as well as feasibility and costs. Conclusion: Telerehabilitation is feasible in people affected by PD. Our analysis of the available data highlighted that telerehabilitation systems are effective in maintaining and/or improving some clinical and non-clinical aspects of PD (balance and gait, speech and voice, quality of life, patient satisfaction). Systematic Review Registration:https://www.crd.york.ac.uk/prospero/, identifier: CRD42020141300.
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Affiliation(s)
- Chiara Vellata
- Istituti Clinici Scientifici Maugeri Spa - Società Benefit, Neurologic Rehabilitation Unit of Veruno Institute, Veruno, Italy
| | - Stefano Belli
- Istituti Clinici Scientifici Maugeri Spa - Società Benefit, Neurologic Rehabilitation Unit of Veruno Institute, Veruno, Italy
| | - Francesca Balsamo
- Istituti Clinici Scientifici Maugeri Spa - Società Benefit, Neurologic Rehabilitation Unit of Veruno Institute, Veruno, Italy
| | - Andrea Giordano
- Istituti Clinici Scientifici Maugeri Spa - Società Benefit, Bioengineering Service, Veruno, Italy
| | - Roberto Colombo
- Istituti Clinici Scientifici Maugeri Spa - Società Benefit, Bioengineering Service, Veruno, Italy
| | - Giorgio Maggioni
- Istituti Clinici Scientifici Maugeri Spa - Società Benefit, Neurologic Rehabilitation Unit of Veruno Institute, Veruno, Italy
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Gedde MH, Husebo BS, Erdal A, Puaschitz NG, Vislapuu M, Angeles RC, Berge LI. Access to and interest in assistive technology for home-dwelling people with dementia during the COVID-19 pandemic (PAN.DEM). Int Rev Psychiatry 2021; 33:404-411. [PMID: 33416012 DOI: 10.1080/09540261.2020.1845620] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
The COVID-19 restrictions affect daily living in Norway, including home-dwelling people with dementia, and researchers conducting clinical trials in dementia care. In this paper, we 1) describe the development of a pandemic cohort (PAN.DEM) incorporated in the LIVE@Home.Path, an ongoing clinical intervention trial on resource utilisation including home-dwelling people with dementia and their caregivers (N = 438 dyads), 2) describe pre-pandemic use of assistive technology and 3) explore the extent to which COVID-19 restrictions increase caregivers interest in innovation in the PAN.DEM cohort (N = 126). Our main finding is that assistive technology is available to 71% pre-pandemic; the vast majority utilise traditional stove guards and safety alarms, only a few operate sensor technology, including GPS, fall detectors or communication aids. In response to COVID-19, 17% show increased interest in technology; being less familiar with operating a telephone and having higher cognitive functioning are both associated with increased interest. We conclude that wearable and sensor technology has not yet been fully implemented among people with dementia in Norway, and few caregivers show increased interest under the restrictions. Clinicaltrials.gov (NCT0404336).
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Affiliation(s)
- Marie H Gedde
- Centre for Elderly and Nursing Home Medicine, Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.,Haraldsplass Deaconess Hospital, Bergen, Norway
| | - Bettina S Husebo
- Centre for Elderly and Nursing Home Medicine, Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.,Municipality of Bergen, Bergen, Norway
| | - Ane Erdal
- Centre for Elderly and Nursing Home Medicine, Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
| | - Nathalie G Puaschitz
- Centre for Care Research, Western Norway University of Applied Sciences, Bergen, Norway
| | - Maarja Vislapuu
- Centre for Elderly and Nursing Home Medicine, Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
| | | | - Line I Berge
- Centre for Elderly and Nursing Home Medicine, Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.,NKS Olaviken Gerontopsychiatric Hospital, Askoy, Norway
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Digital Technology in Movement Disorders: Updates, Applications, and Challenges. Curr Neurol Neurosci Rep 2021; 21:16. [PMID: 33660110 PMCID: PMC7928701 DOI: 10.1007/s11910-021-01101-6] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/21/2021] [Indexed: 12/14/2022]
Abstract
Purpose of Review Digital technology affords the opportunity to provide objective, frequent, and sensitive assessment of disease outside of the clinic environment. This article reviews recent literature on the application of digital technology in movement disorders, with a focus on Parkinson’s disease (PD) and Huntington’s disease. Recent Findings Recent research has demonstrated the ability for digital technology to discriminate between individuals with and without PD, identify those at high risk for PD, quantify specific motor features, predict clinical events in PD, inform clinical management, and generate novel insights. Summary Digital technology has enormous potential to transform clinical research and care in movement disorders. However, more work is needed to better validate existing digital measures, including in new populations, and to develop new more holistic digital measures that move beyond motor features.
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Powers R, Etezadi-Amoli M, Arnold EM, Kianian S, Mance I, Gibiansky M, Trietsch D, Alvarado AS, Kretlow JD, Herrington TM, Brillman S, Huang N, Lin PT, Pham HA, Ullal AV. Smartwatch inertial sensors continuously monitor real-world motor fluctuations in Parkinson's disease. Sci Transl Med 2021; 13:13/579/eabd7865. [PMID: 33536284 DOI: 10.1126/scitranslmed.abd7865] [Citation(s) in RCA: 82] [Impact Index Per Article: 27.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Accepted: 01/11/2021] [Indexed: 12/19/2022]
Abstract
Longitudinal, remote monitoring of motor symptoms in Parkinson's disease (PD) could enable more precise treatment decisions. We developed the Motor fluctuations Monitor for Parkinson's Disease (MM4PD), an ambulatory monitoring system that used smartwatch inertial sensors to continuously track fluctuations in resting tremor and dyskinesia. We designed and validated MM4PD in 343 participants with PD, including a longitudinal study of up to 6 months in a 225-subject cohort. MM4PD measurements correlated to clinical evaluations of tremor severity (ρ = 0.80) and mapped to expert ratings of dyskinesia presence (P < 0.001) during in-clinic tasks. MM4PD captured symptom changes in response to treatment that matched the clinician's expectations in 94% of evaluated subjects. In the remaining 6% of cases, symptom data from MM4PD identified opportunities to make improvements in pharmacologic strategy. These results demonstrate the promise of MM4PD as a tool to support patient-clinician communication, medication titration, and clinical trial design.
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Affiliation(s)
| | | | | | - Sara Kianian
- Apple Inc., Cupertino, CA 95014, USA.,Renaissance School of Medicine, Stony Brook University, Stony Brook, NY 11794, USA
| | | | | | | | | | | | - Todd M Herrington
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA.,Department of Neurology, Harvard Medical School, Boston, MA 02115, USA
| | - Salima Brillman
- Parkinson's Disease and Movement Center of Silicon Valley, Menlo Park, CA 94025, USA
| | - Nengchun Huang
- Silicon Valley Parkinson's Center, Los Gatos, CA 95032, USA
| | - Peter T Lin
- Silicon Valley Parkinson's Center, Los Gatos, CA 95032, USA
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Dahodwala N, Jahnke J, Pettit AR, Li P, Ladage VP, Kandukuri PL, Bao Y, Zamudio J, Jalundhwala YJ, Doshi JA. Low Sustainment of High-Dose Oral Medication Regimens for Advanced Parkinson's Disease in Medicare Beneficiaries. JOURNAL OF PARKINSONS DISEASE 2021; 11:675-684. [PMID: 33386811 DOI: 10.3233/jpd-202147] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Increasing doses of oral antiparkinson medications are indicated in advanced Parkinson's disease (PD), but little is known about sustainment of high-dose regimens. OBJECTIVE To investigate sustainment of high-dose oral medication regimens in Medicare beneficiaries with incident advanced PD. METHODS This retrospective cohort study utilized 100%fee-for-service Medicare claims from 2011-2013. We identified advanced PD using a pharmacy claims-based proxy and selected patients who initiated a new high-dose oral medication regimen (daily levodopa equivalent dose [LED] >1000 mg/day for ≥30 days) in 2012. In the following 12 months, we examined: 1) annual proportion of days covered (PDC)≥0.80 and 2) presence of a ≥ 90 day continuous gap at varying dosage thresholds: the initial >1000 mg/day, >800 mg/day, >500 mg/day, or >0 mg/day. RESULTS We identified 9,405 patients with advanced PD (mean age 77.4 [SD 6.8] years; 53%men). Only 5%maintained a regimen of >1000 mg/day at PDC ≥0.80; 75% had a ≥ 90-day gap in that dosage level. At a dosage threshold of >800 mg/day, 20% had a PDC ≥0.80 and 53% had a ≥ 90-day gap; at >500 mg/day, 56% had a PDC ≥0.80 and 19%had a ≥ 90-day gap; and at >0 mg/day (any dose), 76% had a PDC ≥0.80 and only 10%had a≥90-day gap. CONCLUSION Few patients with advanced PD sustained a high-dose oral medication regimen in the year following initiation, but most sustained a substantially lower-dose regimen. Strategies to improve advanced PD treatment are needed.
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Affiliation(s)
- Nabila Dahodwala
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA
| | - Jordan Jahnke
- Division of General Internal Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Amy R Pettit
- Center for Public Health Initiatives, University of Pennsylvania, Philadelphia, PA, USA
| | - Pengxiang Li
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA.,Division of General Internal Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Vrushabh P Ladage
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA.,Division of General Internal Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | | | | | | | - Jalpa A Doshi
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA.,Division of General Internal Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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12
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The association between overnight fasting and body mass index in older adults: the interaction between duration and timing. Int J Obes (Lond) 2020; 45:555-564. [PMID: 33214704 DOI: 10.1038/s41366-020-00715-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 10/14/2020] [Accepted: 11/02/2020] [Indexed: 12/11/2022]
Abstract
BACKGROUND Circadian rhythms play an important role in the regulation of eating and fasting, and mistimed dietary intakes may be detrimental to metabolic health. Extended overnight fasting has been proposed as a strategy to better align the eating-fasting cycle with the internal circadian clock, and both observational and experimental studies have linked longer overnight fasting with lower body weight. However, it remains unclear if the timing of overnight fasting modifies the relationship between fasting duration and weight outcomes. METHODS The current study included 495 men and 499 women age 50-74 years. Dietary intake over 12 months was assessed by 24-h dietary recalls every two months, and body-mass index was measured at the beginning, middle and end of the study. Logistic regression was used to estimate the relationship between overnight fasting duration and the likelihood of being overweight or obesity adjusted for multiple confounders, and assessed whether the relationship was modified by the timing of overnight fasting, measured as the midpoint of the fasting period. RESULTS Among participants with early overnight fasting (midpoint < 02:19 am), a longer fasting duration was associated with lower odds of overweight and obesity; while among those with late fasting (≥02:19 am), longer fasting was associated with higher odds of overweight and obesity. Specifically, when compared to the shortest quintile of overnight fasting duration, the longest quintile was associated with a 53% reduction in the odds of overweight and obesity in the early fasting group (OR = 0.47, 95% CI = 0.23, 0.97), but a 2.36-fold increase in the late fasting group (OR = 3.36, 95% CI = 1.48, 7.62). Additionally adjusting for dietary intakes during morning and late evening periods did not affect the observed associations. CONCLUSIONS Longer overnight fasting was associated with a reduced likelihood of being overweight or obese, but only among those with an early timing of fasting.
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13
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Luis-Martínez R, Monje MHG, Antonini A, Sánchez-Ferro Á, Mestre TA. Technology-Enabled Care: Integrating Multidisciplinary Care in Parkinson's Disease Through Digital Technology. Front Neurol 2020; 11:575975. [PMID: 33250846 PMCID: PMC7673441 DOI: 10.3389/fneur.2020.575975] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Accepted: 08/24/2020] [Indexed: 11/13/2022] Open
Abstract
Parkinson's disease (PD) management requires the involvement of movement disorders experts, other medical specialists, and allied health professionals. Traditionally, multispecialty care has been implemented in the form of a multidisciplinary center, with an inconsistent clinical benefit and health economic impact. With the current capabilities of digital technologies, multispecialty care can be reshaped to reach a broader community of people with PD in their home and community. Digital technologies have the potential to connect patients with the care team beyond the traditional sparse clinical visit, fostering care continuity and accessibility. For example, video conferencing systems can enable the remote delivery of multispecialty care. With big data analyses, wearable and non-wearable technologies using artificial intelligence can enable the remote assessment of patients' conditions in their natural home environment, promoting a more comprehensive clinical evaluation and empowering patients to monitor their disease. These advances have been defined as technology-enabled care (TEC). We present examples of TEC under development and describe the potential challenges to achieve a full integration of technology to address complex care needs in PD.
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Affiliation(s)
- Raquel Luis-Martínez
- Department of Neurosciences, University of Basque Country (UPV/EHU), Leioa, Spain
- Department of Neurosciences (DNS), Padova University, Padova, Italy
| | - Mariana H G Monje
- HM CINAC, Hospital Universitario HM Puerta del Sur, Universidad CEU-San Pablo, Madrid, Spain
| | - Angelo Antonini
- Department of Neurosciences (DNS), Padova University, Padova, Italy
| | - Álvaro Sánchez-Ferro
- HM CINAC, Hospital Universitario HM Puerta del Sur, Universidad CEU-San Pablo, Madrid, Spain
| | - Tiago A Mestre
- Division of Neurology, Department of Medicine, The Ottawa Hospital Research Institute, Parkinson's Disease and Movement Disorders Center, The University of Ottawa Brain Research Institute, Ottawa, ON, Canada
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14
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Management of Parkinson's disease patients after DBS by remote programming: preliminary application of single center during quarantine of 2019-nCoV. J Neurol 2020; 268:1295-1303. [PMID: 33104873 PMCID: PMC7586381 DOI: 10.1007/s00415-020-10273-z] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2020] [Revised: 09/13/2020] [Accepted: 10/12/2020] [Indexed: 02/07/2023]
Abstract
Introduction Deep brain stimulation (DBS) is an effective treatment for patients with Parkinson’s disease (PD). On time follow-up and timely programing of symptoms are important measures to maintain the effectiveness of DBS. Due to the highly contagious nature of 2019-nCoV, patients were quarantined. With the help of Internet technologies, we continued to provide motor and non-motor symptom assessment and remote programming services for postsurgical PD-DBS patients during this extraordinary period. Methods A retrospective analysis was performed on postsurgical PD-DBS patients who could not come to our hospital for programming due to the impact of the 2019-nCoV. The differences between the pre- and post-programming groups were analyzed. We designed a 5-level Likert rating scale to evaluate the effects and convenience of the remote programming and Internet self-evaluation procedures. Results Of the 36 patients engaged in the remote programming, 32 patients met the inclusion criteria. Four of the 32 patients set initiated stimulation parameters, and the other 28 patients had significant improvement in UPDRS-III. Nearly all the 28 patients were satisfied with the effect of the remote programming. Most of the patients were willing to use remote programming again. Conclusion Remote programming based on the online evaluation of patient’s symptoms can help improve motor symptoms of postsurgical DBS patients with PD during the quarantine period caused by 2019-nCoV. Electronic supplementary material The online version of this article (10.1007/s00415-020-10273-z) contains supplementary material, which is available to authorized users.
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15
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Adler DA, Ben-Zeev D, Tseng VWS, Kane JM, Brian R, Campbell AT, Hauser M, Scherer EA, Choudhury T. Predicting Early Warning Signs of Psychotic Relapse From Passive Sensing Data: An Approach Using Encoder-Decoder Neural Networks. JMIR Mhealth Uhealth 2020; 8:e19962. [PMID: 32865506 PMCID: PMC7490673 DOI: 10.2196/19962] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 07/01/2020] [Accepted: 07/24/2020] [Indexed: 01/16/2023] Open
Abstract
Background Schizophrenia spectrum disorders (SSDs) are chronic conditions, but the severity of symptomatic experiences and functional impairments vacillate over the course of illness. Developing unobtrusive remote monitoring systems to detect early warning signs of impending symptomatic relapses would allow clinicians to intervene before the patient’s condition worsens. Objective In this study, we aim to create the first models, exclusively using passive sensing data from a smartphone, to predict behavioral anomalies that could indicate early warning signs of a psychotic relapse. Methods Data used to train and test the models were collected during the CrossCheck study. Hourly features derived from smartphone passive sensing data were extracted from 60 patients with SSDs (42 nonrelapse and 18 relapse >1 time throughout the study) and used to train models and test performance. We trained 2 types of encoder-decoder neural network models and a clustering-based local outlier factor model to predict behavioral anomalies that occurred within the 30-day period before a participant's date of relapse (the near relapse period). Models were trained to recreate participant behavior on days of relative health (DRH, outside of the near relapse period), following which a threshold to the recreation error was applied to predict anomalies. The neural network model architecture and the percentage of relapse participant data used to train all models were varied. Results A total of 20,137 days of collected data were analyzed, with 726 days of data (0.037%) within any 30-day near relapse period. The best performing model used a fully connected neural network autoencoder architecture and achieved a median sensitivity of 0.25 (IQR 0.15-1.00) and specificity of 0.88 (IQR 0.14-0.96; a median 108% increase in behavioral anomalies near relapse). We conducted a post hoc analysis using the best performing model to identify behavioral features that had a medium-to-large effect (Cohen d>0.5) in distinguishing anomalies near relapse from DRH among 4 participants who relapsed multiple times throughout the study. Qualitative validation using clinical notes collected during the original CrossCheck study showed that the identified features from our analysis were presented to clinicians during relapse events. Conclusions Our proposed method predicted a higher rate of anomalies in patients with SSDs within the 30-day near relapse period and can be used to uncover individual-level behaviors that change before relapse. This approach will enable technologists and clinicians to build unobtrusive digital mental health tools that can predict incipient relapse in SSDs.
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Affiliation(s)
| | - Dror Ben-Zeev
- BRiTE Center, Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States
| | | | - John M Kane
- Department of Psychiatry, The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, United States
| | - Rachel Brian
- BRiTE Center, Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States
| | | | - Marta Hauser
- Vanguard Research Group, Glen Oaks, NY, United States
| | - Emily A Scherer
- Biomedical Data Science Department, Dartmouth Geisel School of Medicine, Hanover, NH, United States
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16
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Gatsios D, Antonini A, Gentile G, Marcante A, Pellicano C, Macchiusi L, Assogna F, Spalletta G, Gage H, Touray M, Timotijevic L, Hodgkins C, Chondrogiorgi M, Rigas G, Fotiadis DI, Konitsiotis S. Feasibility and Utility of mHealth for the Remote Monitoring of Parkinson Disease: Ancillary Study of the PD_manager Randomized Controlled Trial. JMIR Mhealth Uhealth 2020; 8:e16414. [PMID: 32442154 PMCID: PMC7367523 DOI: 10.2196/16414] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Revised: 12/05/2019] [Accepted: 02/07/2020] [Indexed: 12/19/2022] Open
Abstract
Background Mobile health, predominantly wearable technology and mobile apps, have been considered in Parkinson disease to provide valuable ecological data between face-to-face visits and improve monitoring of motor symptoms remotely. Objective We explored the feasibility of using a technology-based mHealth platform comprising a smartphone in combination with a smartwatch and a pair of smart insoles, described in this study as the PD_manager system, to collect clinically meaningful data. We also explored outcomes and disease-related factors that are important determinants to establish feasibility. Finally, we further validated a tremor evaluation method with data collected while patients performed their daily activities. Methods PD_manager trial was an open-label parallel group randomized study.The mHealth platform consists of a wristband, a pair of sensor insoles, a smartphone (with dedicated mobile Android apps) and a knowledge platform serving as the cloud backend. Compliance was assessed with statistical analysis and the factors affecting it using appropriate regression analysis. The correlation of the scores of our previous algorithm for tremor evaluation and the respective Unified Parkinson’s Disease Rating Scale estimations by clinicians were explored. Results Of the 75 study participants, 65 (87%) completed the protocol. They used the PD_manager system for a median 11.57 (SD 3.15) days. Regression analysis suggests that the main factor associated with high use was caregivers’ burden. Motor Aspects of Experiences of Daily Living and patients’ self-rated health status also influence the system’s use. Our algorithm provided clinically meaningful data for the detection and evaluation of tremor. Conclusions We found that PD patients, regardless of their demographics and disease characteristics, used the system for 11 to 14 days. The study further supports that mHealth can be an effective tool for the ecologically valid, passive, unobtrusive monitoring and evaluation of symptoms. Future studies will be required to demonstrate that an mHealth platform can improve disease management and care. Trial Registration ISRCTN Registry ISRCTN17396879; http://www.isrctn.com/ISRCTN17396879 International Registered Report Identifier (IRRID) RR2-10.1186/s13063-018-2767-4
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Affiliation(s)
- Dimitris Gatsios
- Department of Neurology, Medical School, University of Ioannina, Ioannina, Greece.,Unit of Medical Technology and Intelligent Information System, Department of Materials Science and Engineering, University of Ioannina, Ioannina, Greece
| | - Angelo Antonini
- Department of Neuroscience, University of Padua, Padua, Italy.,San Camillo Hospital Istituto Di Ricovero e Cura a Carattere Scientifico, Venice, Italy
| | - Giovanni Gentile
- Department of Neuroscience, University of Padua, Padua, Italy.,San Camillo Hospital Istituto Di Ricovero e Cura a Carattere Scientifico, Venice, Italy
| | - Andrea Marcante
- San Camillo Hospital Istituto Di Ricovero e Cura a Carattere Scientifico, Venice, Italy
| | - Clelia Pellicano
- Laboratory of Neuropsychiatry, Fondazione Santa Lucia Istituto Di Ricovero e Cura a Carattere Scientifico, Rome, Italy
| | - Lucia Macchiusi
- Laboratory of Neuropsychiatry, Fondazione Santa Lucia Istituto Di Ricovero e Cura a Carattere Scientifico, Rome, Italy
| | - Francesca Assogna
- Laboratory of Neuropsychiatry, Fondazione Santa Lucia Istituto Di Ricovero e Cura a Carattere Scientifico, Rome, Italy
| | - Gianfranco Spalletta
- Laboratory of Neuropsychiatry, Fondazione Santa Lucia Istituto Di Ricovero e Cura a Carattere Scientifico, Rome, Italy
| | - Heather Gage
- Surrey Health Economics Centre, Department of Clinical and Experimental Medicine, University of Surrey, Guildford, United Kingdom
| | - Morro Touray
- Surrey Health Economics Centre, Department of Clinical and Experimental Medicine, University of Surrey, Guildford, United Kingdom
| | - Lada Timotijevic
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom
| | - Charo Hodgkins
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom
| | - Maria Chondrogiorgi
- Department of Neurology, Medical School, University of Ioannina, Ioannina, Greece
| | - George Rigas
- Unit of Medical Technology and Intelligent Information System, Department of Materials Science and Engineering, University of Ioannina, Ioannina, Greece
| | - Dimitrios I Fotiadis
- Unit of Medical Technology and Intelligent Information System, Department of Materials Science and Engineering, University of Ioannina, Ioannina, Greece.,Department of Biomedical Research, Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology-Hellas, Ioannina, Greece
| | - Spyridon Konitsiotis
- Department of Neurology, Medical School, University of Ioannina, Ioannina, Greece
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17
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Antonini A. Health care for chronic neurological patients after COVID-19. Lancet Neurol 2020; 19:562-563. [PMID: 32464102 PMCID: PMC7247784 DOI: 10.1016/s1474-4422(20)30157-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Accepted: 04/20/2020] [Indexed: 01/25/2023]
Affiliation(s)
- Angelo Antonini
- Department of Neuroscience, University of Padua, Padua 35138, Italy.
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18
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Fasano A, Antonini A, Katzenschlager R, Krack P, Odin P, Evans AH, Foltynie T, Volkmann J, Merello M. Management of Advanced Therapies in Parkinson's Disease Patients in Times of Humanitarian Crisis: The COVID-19 Experience. Mov Disord Clin Pract 2020; 7:361-372. [PMID: 32373652 DOI: 10.1002/mdc3.12965] [Citation(s) in RCA: 83] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Accepted: 04/17/2020] [Indexed: 12/22/2022] Open
Abstract
Background Although the COVID-19 pandemic is affecting a relatively small proportion of the global population, its effects have already reached everyone. The pandemic has the potential to differentially disadvantage chronically ill patients, including those with Parkinson's disease (PD). The first health care reaction has been to limit access to clinics and neurology wards to preserve fragile patients with PD from being infected. In some regions, the shortage of medical staff has also forced movement disorders neurologists to provide care for patients with COVID-19. Objective To share the experience of various movement disorder neurologists operating in different world regions and provide a common approach to patients with PD, with a focus on those already on advanced therapies, which may serve as guidance in the current pandemic and for emergency situations that we may face in the future. Conclusion Most of us were unprepared to deal with this condition given that in many health care systems, telemedicine has been only marginally available or only limited to email or telephone contacts. In addition, to ensure sufficient access to intensive care unit beds, most elective procedures (including deep brain stimulation or the initiation of infusion therapies) have been postponed. We all hope there will soon be a time when we will return to more regular hospital schedules. However, we should consider this crisis as an opportunity to change our approach and encourage our hospitals and health care systems to facilitate the remote management of chronic neurological patients, including those with advanced PD.
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Affiliation(s)
- Alfonso Fasano
- Edmond J. Safra Program in Parkinson's Disease and the Morton and Gloria Shulman Movement Disorders Centre, Toronto Western Hospital, University Health Network, Division of Neurology University of Toronto Toronto Ontario Canada.,Krembil Brain Institute Toronto Ontario Canada.,The Center for Advancing Neurotechnological Innovation to Application Toronto Ontario Canada
| | | | - Regina Katzenschlager
- Department of Neurology and Karl Landsteiner Institute for Neuroimmunological and Neurodegenerative Disorders Donauspital Vienna Austria
| | - Paul Krack
- Department of Neurology, Center for Parkinson's Disease and Movement Disorders Inselspital, Bern University Hospital, University of Bern Bern Switzerland
| | - Per Odin
- Division of Neurology, Department of Clinical Sciences Lund Lund University Lund Sweden
| | - Andrew H Evans
- Department of Neurology the Royal Melbourne Hospital Victoria Australia
| | - Thomas Foltynie
- Department of Clinical & Movement Neurosciences University College London Institute of Neurology, Queen Square London United Kingdom
| | - Jens Volkmann
- Neurologischen Klinik Universitätsklinikum Würzburg Würzburg Germany
| | - Marcelo Merello
- Movement Disorders Section Fleni Buenos Aires Argentina.,Consejo Nacional de Investigaciones Científicas y Técnicas Buenos Aires Argentina
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19
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Marxreiter F, Buttler U, Gassner H, Gandor F, Gladow T, Eskofier B, Winkler J, Ebersbach G, Klucken J. The Use of Digital Technology and Media in German Parkinson’s Disease Patients. JOURNAL OF PARKINSONS DISEASE 2020; 10:717-727. [DOI: 10.3233/jpd-191698] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Affiliation(s)
- Franz Marxreiter
- Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Ulrike Buttler
- Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Heiko Gassner
- Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Florin Gandor
- Movement Disorders Clinic, Beelitz-Heilstaetten, Beelitz, Germany
| | - Till Gladow
- Medical Valley Digital Health Application Center, Bamberg, Germany
| | - Bjoern Eskofier
- Machine Learning and Data Analytics Lab, Department of Computer Science, FAU, Germany
| | - Jürgen Winkler
- Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Georg Ebersbach
- Movement Disorders Clinic, Beelitz-Heilstaetten, Beelitz, Germany
| | - Jochen Klucken
- Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
- Research Group Digital Health Pathways, Fraunhofer IIS, Erlangen, Germany
- Medical Valley Digital Health Application Center, Bamberg, Germany
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