Abstract

Balance confidence and fear of falling are factors associated with recurrent falls in people with Parkinson disease (PD). However, the accuracy for predicting falls on the basis of self-report measures has not been widely investigated. The study objectives were: (1) to compare the accuracy of the Activities-specific Balance Confidence Scale (ABC) and the Falls Efficacy Scale-International (FES-I) with that of the Berg Balance Scale (BBS), Dynamic Gait Index (DGI), Functional Reach Test (FRT), and Timed "Up & Go" Test (TUG) for predicting recurrent falls in people with PD and (2) to explore the ability of combinations of up to 3 tests to predict recurrent falls. This was a prospective cohort study involving 225 people with PD. Participants were assessed with the ABC, FES-I, BBS, FRT, TUG, and DGI. Participants who reported 2 or more falls in the 12-month follow-up period were classified as recurrent fallers. Areas under the receiver operating characteristic curves were determined, and the Akaike information criterion was used to select the best predictive model. Eighty-four participants (37.3%) were classified as recurrent fallers. Areas under the receiver operating characteristic curves for the ABC, FES-I, TUG, FRT, DGI, and BBS were 0.73, 0.74, 0.72, 0.74, 0.76, and 0.79, respectively. Two-test models provided additional discriminating ability compared with individual measures and had Akaike information criterion values similar to those of 3-test models, particularly the combination of the BBS with the FES-I. The lack of an external validation sample was a limitation of this study. The ABC and FES-I demonstrated moderate accuracy in predicting recurrent falls and a predictive ability similar to that of performance-based balance measures, especially the FRT and the TUG. Two-test models showed performance similar to that of 3-test models, suggesting that a combination of 2 measures may improve the ability to predict recurrent falls in people with PD. Specifically, the combination of the BBS with the FES-I may be considered.

Full Text
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