The Mini-BESTest is an independent predictor of falls in Parkinson disease
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Universidade Federal de Minas Gerais
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Artigo de periódico
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Background: Falls in Parkinson Disease (PD) are a complex health problem, with multidimensional causes and consequences. Objectives: To identify the fall predictors in individuals with PD and compare fallers and non-fallers considering their socio-demographic, anthropometric, clinical and functional status. Methods: A 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. Results: Three-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. Conclusion: Besides 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.
Abstract
Assunto
Fisioterapia, Acidentes por quedas, Fatores de risco, Parkinson, Doença de
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Physical therapy, Accidental falls, Risk factors
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https://www.sciencedirect.com/science/article/pii/S1413355518308098?via%3Dihub#!