Larissa Karlla Rodrigues Lopes1, Aline Alvim Scianni2, Lidiane Oliveira Lima3, Raquel de Carvalho Lana2, Fátima Rodrigues-De-Paula2. 1. Department of Physical Therapy, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil. Electronic address: larissakarlla_rl@hotmail.com. 2. Department of Physical Therapy, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil. 3. Department of Physical Therapy, Universidade Federal do Ceará (UFC), Ceará, Brazil.
Abstract
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.
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.
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