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Functional Gait Assessment: Concurrent, Discriminative, and Predictive Validity in Community-dwelling Older Adults

Overview
Journal Phys Ther
Date 2010 Apr 3
PMID 20360052
Citations 106
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Abstract

Background: The Functional Gait Assessment (FGA) is a reliable and valid measure of gait-related activities.

Objective: The purpose of this study was to determine the concurrent, discriminative, and predictive validity of the FGA in community-dwelling older adults.

Design: This was a prospective cohort study.

Methods: Thirty-five older adults aged 60 to 90 years completed the Activities-specific Balance Confidence Scale (ABC), Berg Balance Scale (BBS), Dynamic Gait Index (DGI), Timed "Up & Go" Test (TUG), and Functional Gait Assessment (FGA) during one session. Falls were tracked by having participants complete a monthly fall calendar for 6 months. Spearman correlation coefficients were used to determine concurrent validity among the ABC, BBS, TUG, DGI, and FGA. To determine the optimum scores to classify fall risk, sensitivity (Sn), specificity (Sp), and positive and negative likelihood ratios (LR+ and LR-) were calculated for the FGA in classifying fall risk based on the published criterion scores of the DGI and TUG and for the FGA, TUG, and DGI in identifying prospective falls. Receiver operator curves with area under the curve were used to determine the effectiveness of the FGA in classifying fall risk and of the DGI, TUG, and FGA in identifying prospective falls.

Results: The FGA correlated with the ABC (r=.053, P<.001), BBS (r=.84, P<.001), and TUG (r=-.84, P<.001). An FGA score of <or=22/30 provides both discriminative and predictive validity. The FGA (scores <or=22/30) provided 100% Sn, 72% Sp, LR+ of 3.6, and LR- of 0 to predict prospective falls. Limitations The study was limited by the length of time of follow-up and the small sample size that did not allow for evaluation of criterion scores by decade.

Conclusions: The FGA with a cutoff score of 22/30 is effective in classifying fall risk in older adults and predicting unexplained falls in community-dwelling older adults.

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