Literature DB >> 23939309

Predicting outcomes in Parkinson's disease: comparison of simple motor performance measures and The Unified Parkinson's Disease Rating Scale-III.

Stephen Grill1, Jennifer Weuve, Marc G Weisskopf.   

Abstract

The Unified Parkinson's Disease Rating Scale (UPDRS) part III is the principal motor assessment method for Parkinson's disease (PD), but has recognized limitations including subjectivity and insensitivity. Easy to administer, objective, quantitative tests that are good indicators of PD progression could offer advantages in both clinical and research settings. We administered four simple, motor performance measures--functional reach, timed hall walk, a timed block sort task, and timed dotting--as well as the UPDRS to 609 PD patients of a single neurologist. The unadjusted Spearman correlations of these performance measures with the UPDRS motor score (UPDRS III) ranged from 0.29 to 0.49. Moreover, these measures generally had high reliability on repeated testing. We defined specific outcomes in PD--overall disability, gait instability and falls, as well as non-motor outcomes of depression, dementia, and psychosis, and assessed the ability of the measures to predict these outcomes over the entire follow-up of the cohort (average: 2.4 years) and over the first year of follow-up. The associations between the measures and the outcomes were generally stronger and more precise for the performance measures than for the UPDRS III. A summary score of the performance measures was a particularly good predictor of the outcomes. These motor performance measures could provide a rapid, simple means of assessing PD progression that could benefit both clinical and research endeavors.

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Year:  2011        PMID: 23939309     DOI: 10.3233/JPD-2011-11016

Source DB:  PubMed          Journal:  J Parkinsons Dis        ISSN: 1877-7171            Impact factor:   5.568


  5 in total

1.  Measures of motor segmentation from rapid isometric force pulses are reliable and differentiate Parkinson's disease from age-related slowing.

Authors:  Sherron L Howard; David Grenet; Maria Bellumori; Christopher A Knight
Journal:  Exp Brain Res       Date:  2022-06-29       Impact factor: 2.064

2.  DAT and TH expression marks human Parkinson's disease in peripheral immune cells.

Authors:  Adithya Gopinath; Phillip Mackie; Basil Hashimi; Anna Marie Buchanan; Aidan R Smith; Rachel Bouchard; Gerry Shaw; Martin Badov; Leila Saadatpour; Aryn Gittis; Adolfo Ramirez-Zamora; Michael S Okun; Wolfgang J Streit; Parastoo Hashemi; Habibeh Khoshbouei
Journal:  NPJ Parkinsons Dis       Date:  2022-06-07

3.  Longitudinal clustering analysis and prediction of Parkinson's disease progression using radiomics and hybrid machine learning.

Authors:  Mohammad R Salmanpour; Mojtaba Shamsaei; Ghasem Hajianfar; Hamid Soltanian-Zadeh; Arman Rahmim
Journal:  Quant Imaging Med Surg       Date:  2022-02

4.  The Length of SNCA Rep1 Microsatellite May Influence Cognitive Evolution in Parkinson's Disease.

Authors:  Lucia Corrado; Fabiola De Marchi; Sara Tunesi; Gaia Donata Oggioni; Miryam Carecchio; Luca Magistrelli; Silvana Tesei; Giulio Riboldazzi; Alessio Di Fonzo; Clarissa Locci; Ilaria Trezzi; Roberta Zangaglia; Cristina Cereda; Sandra D'Alfonso; Corrado Magnani; Giacomo P Comi; Giorgio Bono; Claudio Pacchetti; Roberto Cantello; Stefano Goldwurm; Cristoforo Comi
Journal:  Front Neurol       Date:  2018-03-29       Impact factor: 4.003

Review 5.  Nutritional Ketosis in Parkinson's Disease - a Review of Remaining Questions and Insights.

Authors:  Alexander Choi; Mark Hallett; Debra Ehrlich
Journal:  Neurotherapeutics       Date:  2021-07-07       Impact factor: 7.620

  5 in total

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