Citation

Magnani PE, Genovez MB, Porto JM, Zanellato NFG, Alvarenga IC, Freire RC, de Abreu DCC. J. Geriatr. Phys. Ther. 2019; ePub(ePub): ePub.

Affiliation

Department of Health Sciences at the Ribeirão Preto School of Medicine of the University of São Paulo (USP), Ribeirão Preto, São Paulo, Brazil.

Copyright

(Copyright © 2019, American Physical Therapy Association)

DOI

10.1519/JPT.0000000000000236

PMID

31162155

Abstract

BACKGROUND AND PURPOSE: Reference values for the Balance Evaluation Systems Test (BESTest) and the Mini-Balance Evaluation Systems Test (Mini-BESTest) need to be established to predict falls in older adults during every stage of aging. The purpose of this study was to determine the cutoff scores for the BESTest and the Mini-BESTest for community-dwelling older adults in order to predict fall risk.

METHODS: A total of 264 older adults, of both sexes, between the ages of 60 and 102 years, were divided into 4 groups according to age range. After evaluation, participants received telephone follow-up for 6 months to record the number of fall episodes. To define the reference values of the tests in relation to fall risk prediction, a receiver operating characteristic curve was drawn to identify the area under the curve and the sensitivity and specificity of the tests. Statistical analyses were done using SPSS (Version 16.0-SPSS Inc) with a significance level of 5% (P ≤.05).

RESULTS: The cutoff scores to identify older adults with fall risk according to the BESTest and the Mini-BESTest in the different age groups were 99 and 25 points, respectively, for people 60 to 69 years of age, 92 and 23 points for the age group of 70 to 79 years, 85 and 22 points for people 80 to 89 years of age, and 74 and 17 points for people 90 years of age or older.

CONCLUSION: The BESTest and the Mini-BESTest are good tools for predicting fall risk in the 6 months following an initial evaluation in community-dwelling Brazilian older adults. The study also determined that cutoff values vary for different age groups.

Language: en