Citation

Nocera J, Stegemöller EL, Malaty I, Okun M, Marsiske M, Hass C. Arch. Phys. Med. Rehabil. 2013; 94(7): 1300-1305.

Affiliation

VA Rehabilitation R&D Center of Excellence, Atlanta VAMC; Emory University, Department of Neurology. Electronic address: joenocera@emory.edu.

Copyright

(Copyright © 2013, Elsevier Publishing)

DOI

10.1016/j.apmr.2013.02.020

PMID

23473700

Abstract

OBJECTIVE: To investigate the ability of the Timed Up and Go test to identify patients with Parkinson's disease at risk for a fall. This study hypothesized that the Timed Up and Go test may be a reliable clinical tool to predict fall risk in Parkinson's disease. DESIGN: Cross-sectional cohort study. SETTING: Sixteen participating National Parkinson's Foundation Centers of Excellence. PARTICIPANTS: A query yielded a total of 2,985 records (1828 men and 1157 women). From these, 884 were excluded because of a lack of crucial information (age, diagnosis, the presence of deep brain stimulation, disease duration, inability of performing the timed up and go without assistance) at the time of testing leaving 2,097 patients included in the analysis. INTERVENTION: Not applicable. MAIN OUTCOME MEASURES: The primary outcome measure for this study was falls. The chief independent variable was the Timed Up and Go. RESULTS: The initial model examined the prediction of falls from Timed Up and Go, adjusting for all study covariates. The estimated models in the imputed data sets represented a significant improvement above chance (χ2 range (df=17): 531.29 to 542.39, p < .001) suggesting that 74% of participants were accurately classified as a faller or non-faller. The secondary model in which the question of whether the effect of Timed Up and Go was invariant across disease severity demonstrated 75% of participants were accurately classified as a faller or non-faller. Additional analysis revealed a proposed cut score of 11.5 seconds for discrimination of those who did or did not fall. CONCLUSIONS: The findings suggest that the Timed Up and Go test may be an accurate assessments tool to identity those at risk for a fall.

Language: en