Remote Assessment of Disease and Relapse in Epilepsy: Protocol for a Multicenter Prospective Cohort Study
Autor: | Sebastian Böttcher, Sara Simblett, Richard Dobson, Simon Lees, Zulqarnain Rashid, Andreas Schulze-Bonhage, Ann Little, Nikolay V. Manyakov, Sarah Thorpe, Inez Myin-Germeys, Elisa Bruno, Til Wykes, Andrea Biondi, Mark P. Richardson, Gergely Vértes, Amanda Stoneman, Yatharth Ranjan, Aki Rintala, Amos Folarin |
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Rok vydání: | 2020 |
Předmět: |
Telemedicine
020205 medical informatics Computer applications to medicine. Medical informatics R858-859.7 02 engineering and technology 03 medical and health sciences Epilepsy 0302 clinical medicine Quality of life (healthcare) 0202 electrical engineering electronic engineering information engineering medicine Protocol media_common.cataloged_instance European union media_common seizures Protocol (science) Research ethics mobile phone business.industry medical device Usability General Medicine medicine.disease 3. Good health Mood Medicine epilepsy Medical emergency telemedicine business 030217 neurology & neurosurgery |
Zdroj: | JMIR Research Protocols JMIR Research Protocols, Vol 9, Iss 12, p e21840 (2020) |
ISSN: | 1929-0748 |
DOI: | 10.2196/21840 |
Popis: | Background In recent years, a growing body of literature has highlighted the role of wearable and mobile remote measurement technology (RMT) applied to seizure detection in hospital settings, whereas more limited evidence has been produced in the community setting. In clinical practice, seizure assessment typically relies on self-report, which is known to be highly unreliable. Moreover, most people with epilepsy self-identify factors that lead to increased seizure likelihood, including mood, behavior, sleep pattern, and cognitive alterations, all of which are amenable to measurement via multiparametric RMT. Objective The primary aim of this multicenter prospective cohort study is to assess the usability, feasibility, and acceptability of RMT in the community setting. In addition, this study aims to determine whether multiparametric RMT collected in populations with epilepsy can prospectively estimate variations in seizure occurrence and other outcomes, including seizure frequency, quality of life, and comorbidities. Methods People with a diagnosis of pharmacoresistant epilepsy will be recruited in London, United Kingdom, and Freiburg, Germany. Participants will be asked to wear a wrist-worn device and download ad hoc apps developed on their smartphones. The apps will be used to collect data related to sleep, physical activity, stress, mood, social interaction, speech patterns, and cognitive function, both passively from existing smartphone sensors (passive remote measurement technology [pRMT]) and actively via questionnaires, tasks, and assessments (active remote measurement technology [aRMT]). Data will be collected continuously for 6 months and streamed to the Remote Assessment of Disease and Relapse-base (RADAR-base) server. Results The RADAR Central Nervous System project received funding in 2015 from the Innovative Medicines Initiative 2 Joint Undertaking under Grant Agreement No. 115902. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation program and European Federation of Pharmaceutical Industries and Associations. Ethical approval was obtained in London from the Bromley Research Ethics Committee (research ethics committee reference: 19/LO/1884) in January 2020. The first participant was enrolled on September 30, 2020. Data will be collected until September 30, 2021. The results are expected to be published at the beginning of 2022. Conclusions RADAR Epilepsy aims at developing a framework of continuous data collection intended to identify ictal and preictal states through the use of aRMT and pRMT in the real-life environment. The study was specifically designed to evaluate the clinical usefulness of the data collected via new technologies and compliance, technology acceptability, and usability for patients. These are key aspects to successful adoption and implementation of RMT as a new way to measure and manage long-term disorders. International Registered Report Identifier (IRRID) PRR1-10.2196/21840 |
Databáze: | OpenAIRE |
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