Comparing Objective and Subjective Measures of Parkinson's Disease Using the Parkinson's KinetiGraph - Knudson, Mei; Thomsen, Trine Hoermann; Kjaer, Troels Wesenberg (Frontiers in Neurology, 2020)
Background Parkinson’s disease (PD) is a neurodegenerative disease that can lead to impaired motor function and execution of activities of daily living (ADL). Since clinicians typically can only observe patients’ symptoms during visits, prescribed medication schedules may not reflect the full range of symptoms experienced throughout the day. Therefore, objective tools are needed to provide comprehensive symptom data to optimize treatment. One such tool is the Parkinson’s KinetiGraph® (PKG), a wearable sensor that measures motor symptoms of Parkinson’s disease. Objective To build a mathematical model to determine if PKG data measuring Parkinson’s patients’ motor symptoms can predict patients’ ADL impairment. Methods Thirty-four patients with PD wore the PKG device for 7 days while performing their ADL. Patients’ PKG scores for bradykinesia and dyskinesia, as well as their responses to a questionnaire asking if their ADL-level had been impacted by various motor symptoms, were used to build a multiple regression model predicting the patients’ Movement Disorder Society-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) part II scores. Results Calculation of bradykinesia score response to medication showed that the greatest bradykinesia response occurred when the dosage response time was set at 30 minutes. The overall multiple regression model predicting MDS-UPDRS part II score was significant (R2=0.520, p<.001). Conclusion The PKG’s ability to provide motor symptom data that can accurately predict clinical measures of ADL impairment suggests that it has strong potential as a tool for the assessment and management of Parkinson’s disease motor symptoms.