Quantitative mobility measures complement the MDS-UPDRS for characterization of Parkinson's disease heterogeneity. (March 2021)

• Record Type: Journal Article
• Authors: Hill, Emily J.; Mangleburg, C. Grant; Alfradique-Dunham, Isabel; Ripperger, Brittany; Stillwell, Amanda; Saade, Hiba; Rao, Sindhu; Fagbongbe, Oluwafunmiso; von Coelln, Rainer; Tarakad, Arjun; Hunter, Christine; Dawe, Robert J.; Jankovic, Joseph; Shulman, Lisa M.; Buchman, Aron S.; Shulman, Joshua M.
• Is Part Of: Parkinsonism & related disorders. Volume 84(2021)
• Page Start: 105
• Page End: 111
• Publication Date: 2021-03
• Subjects: Parkinson's disease -- Wearable sensors -- Wearables -- Device; Parkinson's disease -- Periodicals; Movement disorders -- Periodicals; Movement Disorders -- Periodicals; Nerve Degeneration -- Periodicals; Nervous System Diseases -- Periodicals; Parkinson Disease -- Periodicals; Tremor -- Periodicals; Parkinson, Maladie de -- Périodiques; Parkinson's disease; 616.833
• DOI: 10.1016/j.parkreldis.2021.02.006
• Languages: English
• ISSNs: 1353-8020

Abstract

Abstract: Introduction: Emerging technologies show promise for enhanced characterization of Parkinson's Disease (PD) motor manifestations. We evaluated quantitative mobility measures from a wearable device compared to the conventional motor assessment, the Movement Disorders Society-Unified PD Rating Scale part III (motor MDS-UPDRS). Methods: We evaluated 176 PD subjects (mean age 65, 65% male, 66% H&Y stage 2) during routine clinic visits using the motor MDS-UPDRS and a 10-min motor protocol with a body-fixed sensor (DynaPort MT, McRoberts BV), including the 32-ft walk, Timed Up and Go (TUG), and standing posture with eyes closed. Regression models examined 12 quantitative mobility measures for associations with (i) motor MDS-UPDRS, (ii) motor subtype (tremor dominant vs. postural instability/gait difficulty), (iii) Montreal Cognitive Assessment (MoCA), and (iv) physical functioning disability (PROMIS-29). All analyses included age, gender, and disease duration as covariates. Models iii-iv were secondarily adjusted for motor MDS-UPDRS. Results: Quantitative mobility measures from gait, TUG transitions, turning, and posture were significantly associated with motor MDS-UPDRS (7 of 12 measures, p < 0.05) and motor subtype (6 of 12 measures, p < 0.05). Compared with motor MDS-UPDRS, several quantitative mobility measures accounted for a 1.5- or 1.9-fold increased variance in either cognition or physical functioning disability, respectively. Among minimally-impaired subjects in the bottom quartile of motor MDS-UPDRS, including subjects with normal gait exam, the measures captured substantial residual motor heterogeneity. Conclusion: Clinic-based quantitative mobility assessments using a wearable sensor captured features of motor performance beyond those obtained with the motor MDS-UPDRS and may offer enhanced characterization of disease heterogeneity. Highlights: Wearable device measures were associated with the motor MDS-UPDRS and PD subtype. Measures explained increased variance in cognition and disability beyond the UPDRS. Wearables detect motor heterogeneity in minimally-impaired subjects with normal gait.