The Mini-BESTest is an independent predictor of falls in Parkinson Disease

Abstract

BackgroundFalls in Parkinson Disease (PD) are a complex health problem, with multidimensional causes and consequences. ObjectivesTo identify the fall predictors in individuals with PD and compare fallers and non-fallers considering their socio-demographic, anthropometric, clinical and functional status. MethodsA multicenter cross-sectional design was employed. Variables included: age, sex, body mass index, PD progression, levodopa dosage, activities limitation and motor impairments (UPDRS ADL/Motor), level of physical activity (human activity profile – HAP), fear of falls (Falls Efficacy Scale-International-FES-I), freezing of gait (Freezing of Gait Questionnaire – FOG-Q), gait speed (10 meters walk test – 10-MWT), lower limb functional strength (Five Times Sit-to-Stand Test – FTSST), balance (Mini-BESTest), mobility (Timed “Up & Go” – TUG) and dual-task dynamic (TUG-DT). Seventeen potential predictors were identified. Logistic regression and ROC curve were applied. ResultsThree-hundred and seventy individuals (44.87% fallers and 55.13% non-fallers) completed the study. Fallers presented worse performance in UPDRS motor/ADL/Total, FES-I, FOG-Q, Mini-BESTest, HAP, TUG and TUG-DT and the majority were inactive. The Mini-BESTest Total was the main independent predictor of falls (OR=0.92; p<0.001; 95% CI=0.89, 0.95). For each one-unit increase in the Mini-BESTest, there was an average reduction of 8% in the probability of being a faller. A cut-off point of 21.5/28 (AUC=0.669, sensitivity 70.7% and specificity 55.1%) was determined. ConclusionBesides characterizing and comparing fallers and non-fallers, this study showed that the Mini-BESTest was the strongest individual predictor of falls in individuals with PD, highlighting the importance of evaluating dynamic balance ability during fall risk assessment.