Objective: Evaluate the utility of wearable digital health technology for identifying and characterizing levodopa-induced dyskinesia in real-world settings.

Background: Patients with Parkinson disease (PwP) frequently face challenges accurately identifying and reporting the timing and severity of motor complications, including dyskinesia and response fluctuations.^1,2 Wearable devices allow collection of objective data from the PwP’s home environment.

Method: This observational, pilot study will include up to 120 PwP who have experienced dyskinesia and have been on levodopa therapy for more than two years. Participants use a HIPAA-compliant, FDA-cleared application³ loaded onto a commonly used smartwatch to passively collect dyskinesia and tremor data during daily activities and sleep. Participants also record symptoms, medication usage, and quality of life data through electronic questionnaires. Standard clinical assessments from routine healthcare provider visits complement this data. Regular summary reports generated from the collected data are provided to participants and their healthcare providers to support symptom management and clinical decisions. The study is conducted remotely without additional clinical visits for up to 2 years. Results will also be compared with clinician assessments collected during standard of care visits. Clinician and PwP user feedback are also periodically gathered to improve the platform and utility of data reporting.

Results: The study aims to assess the feasibility and clinical utility of wearable device systems in accurately characterizing dyskinesia and PD motor symptoms. Analyses will utilize objective wearable metrics, patient-reported questionnaire data, and clinician documentation to evaluate the real-world applicability and accuracy of wearable device systems.

Conclusion: Wearable devices that can accurately identify PD motor states and provide clinicians with easily readable and actionable outputs have the potential to substantially enhance patient care as well as clinical trial assessments. Data from this study will be used to assess the real-world accuracy and utility of a consumer wearable platform to enhance efficient delivery of care.

References: 1. M. K. Erb, D. R. Karlin, B. K. Ho, K. C. Thomas, F. Parisi, G. P. Vergara-Diaz, J.-F. Daneault, P. W. Wacnik, H. Zhang, T. Kangarloo, C. Demanuele, C. R. Brooks, C. N. Detheridge, N. S. Kabiri, J. S. Bhangu, P. Bonato, mHealth and wearable technology should replace motor diaries to track motor fluctuations in Parkinson’s disease. NPJ Digit. Med. 3, 6 (2020).
2. S. Pietracupa, A. Fasano, G. Fabbrini, M. Sarchioto, M. Bloise, A. Latorre, M. Altieri, M. Bologna, A. Berardelli, Poor self-awareness of levodopa-induced dyskinesias in Parkinson’s disease: Clinical features and mechanisms. Parkinsonism Relat. Disord. 19, 1004–1008 (2013)
3. Rune labs secures FDA clearance for Parkinson’s disease monitoring through StrivePD ecosystem on Apple Watch. News release. Rune Labs. June 13, 2022. Accessed June 20, 2022. https://www.prnewswire.com/news-releases/rune-labs-secures-fda-clearance-for-parkinsons-disease-monitoring-through-strivepd-ecosystem-on-apple-watch-301566472.html

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MDS Abstracts - https://www.mdsabstracts.org/abstract/longitudinal-remote-monitoring-with-wearable-technology-in-parkinson-disease-initiation-of-a-dyskinesia-insight-network-observational-study/