Abbreviated MDS-UPDRS for Remote Monitoring in PD Identified Using Exhaustive Computational Search

Gareth Morinan; Robert A Hauser; Anette Schrag; Jingxuan Tang; Jonathan O'Keeffe; Mds-Nms Scale Development Study Group

doi:10.1155/2022/2920255

Abbreviated MDS-UPDRS for Remote Monitoring in PD Identified Using Exhaustive Computational Search

Parkinsons Dis. 2022 Jun 7:2022:2920255. doi: 10.1155/2022/2920255. eCollection 2022.

Authors

Gareth Morinan¹, Robert A Hauser², Anette Schrag³, Jingxuan Tang¹, Jonathan O'Keeffe¹, Mds-Nms Scale Development Study Group⁴

Affiliations

¹ Machine Medicine Technologies Ltd., The Leather Market Unit 1.1.1, 11/13 Weston Street, London SE1 3ER, UK.
² Parkinson's Disease and Movement Disorders Center, Department of Neurology, Parkinson Foundation Center of Excellence, University of South Florida, 4001 E Fletcher Ave, Tampa, FL 33613, USA.
³ Department of Clinical and Movement Neurosciences, Institute of Neurology, University College London, Queen Square, London WC1N 3AR, UK.
⁴ Movement Disorder Society, 555 East Wells Street, Suite 1100 Milwaukee, WI 53202-3823, USA.

Abstract

Background: The Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) comprises 50 items, consisting of historical questions and motor ratings, typically taking around 30 minutes to complete. We sought to identify an abbreviated version that could facilitate use in clinical practice or used remotely via telemedicine.

Methods: To create an 8-item version we conducted an "exhaustive search" of all possible subsets. We measured explained variance in comparison to the 50-item version using linear regression, with the "optimal" subset maximising this while also meeting remote assessment practicality constraints. The subset was identified using a dataset collected by the Parkinson's Progression Markers Initiative and validated using an MDS Non-Motor Symptoms Scale validation study dataset.

Results: The optimal remote version comprised items from all parts of the MDS-UPDRS and was found to act as an unbiased estimator of the total 50-item score. This version had an explained variance score of 0.844 and was highly correlated with the total MDS-UPDRS score (Pearson's r = 0.919, p-value <0.0001). Another subset that maximised explained variance score without adhering to remote assessment practicality constraints provided similar results.

Conclusion: This result demonstrates that the total scores of an abbreviated form identified by computational statistics had high agreement with the MDS-UPDRS total score. Whilst it cannot capture the richness of information of the full MDS-UPDRS, it can be used to create a total score where practicality limits the application of the full MDS-UPDRS, such as remote monitoring. Further validation will be required, including in specific subgroups and advanced disease stages, and full validation of clinimetric properties.