Quantitative mobility measures complement the MDS-UPDRS for characterization of Parkinson disease heterogeneity
Emily J. Hill,
Carl Grant Mangleburg,
Rainer von Coelln,
Robert J Dawe,
Lisa M. Shulman,
Aron S. Buchman,
Joshua M. Shulman
Posted 17 Aug 2020
medRxiv DOI: 10.1101/2020.08.16.20175596
Posted 17 Aug 2020
Introduction: Emerging technologies show promise for enhanced characterization of Parkinson 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 subjects with PD (mean age 65, 65% male, 66% H&Y stage 2) at the time of routine clinic visits using the motor MDS-UPDRS and a structured 10-minute motor protocol, which included a 32-ft walk, Timed Up and Go (TUG), and standing posture with eyes closed, while wearing a body-fixed sensor (DynaPort MT, McRoberts BV). 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 subtype (6 of 12 measures, p<0.05). Compared with motor MDS-UPDRS, several quantitative mobility measures accounted for ~1.5-fold increased variance in either cognition or physical functioning disability. Among minimally-impaired subjects within 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.
- Downloaded 238 times
- Download rankings, all-time:
- Site-wide: 122,872
- In neurology: 496
- Year to date:
- Site-wide: 94,879
- Since beginning of last month:
- Site-wide: 74,927
Downloads over time
Distribution of downloads per paper, site-wide
- 27 Nov 2020: The website and API now include results pulled from medRxiv as well as bioRxiv.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!