Quantitative mobility measures complement the MDS-UPDRS for characterization of Parkinson's disease heterogeneity
von Coelln, R.
JournalParkinsonism and Related Disorders
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AbstractIntroduction: 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. Copyright 2021 The Author(s)
SponsorsEJH was supported by the Parkinson Study Group/Parkinson's Foundation Mentored Clinical Research Award and the NHGRI Medical Genetics Research Fellowship ( T32GM007526-41 ). JMS was supported by Huffington Foundation and a Career Award for Medical Scientists from the Burroughs Welcome Fund . LMS was supported by the NIH and the Rosalyn Newman Foundation . RJD was supported by a NIA Mentored Quantitative Research Development Award ( K25AG61254 ). AB received support from NIH ( R01AG056352 , R01AG017917 , RF1AG022018 ). JJ received funding from AbbVie Inc , CHDI Foundation , Dystonia Coalition , Hoffmann-La Roche Ltd , Michael J Fox Foundation , NIH , Parkinson's Foundation , Parkinson Study Group, Roche, and Teva Pharmaceutical Industries Ltd .
Identifier to cite or link to this itemhttp://hdl.handle.net/10713/15208
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