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Please use this identifier to cite or link to this item: http://hdl.handle.net/1843/42623
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dc.creatorLarissa Karlla Rodrigues Lopespt_BR
dc.creatorAline Alvim Sciannipt_BR
dc.creatorLidiane Oliveira Limapt_BR
dc.creatorRaquel de Carvalho Lanapt_BR
dc.creatorFatima Rodrigues de Paulapt_BR
dc.date.accessioned2022-06-23T17:34:41Z-
dc.date.available2022-06-23T17:34:41Z-
dc.date.issued2020-09-
dc.citation.volume24pt_BR
dc.citation.issue5pt_BR
dc.citation.spage433pt_BR
dc.citation.epage440pt_BR
dc.identifier.doihttps://doi.org/10.1016/j.bjpt.2019.07.006pt_BR
dc.identifier.issn1413-3555pt_BR
dc.identifier.urihttp://hdl.handle.net/1843/42623-
dc.description.resumoBackground: 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.pt_BR
dc.description.sponsorshipCNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológicopt_BR
dc.description.sponsorshipFAPEMIG - Fundação de Amparo à Pesquisa do Estado de Minas Geraispt_BR
dc.description.sponsorshipCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superiorpt_BR
dc.format.mimetypepdfpt_BR
dc.languageengpt_BR
dc.publisherUniversidade Federal de Minas Geraispt_BR
dc.publisher.countryBrasilpt_BR
dc.publisher.departmentEEF - DEPARTAMENTO DE FISIOTERAPIApt_BR
dc.publisher.initialsUFMGpt_BR
dc.relation.ispartofBrazilian Journal of Physical Therapypt_BR
dc.rightsAcesso Abertopt_BR
dc.subjectPhysical therapypt_BR
dc.subjectAccidental fallspt_BR
dc.subjectRisk factorspt_BR
dc.subject.otherFisioterapiapt_BR
dc.subject.otherAcidentes por quedaspt_BR
dc.subject.otherFatores de riscopt_BR
dc.subject.otherParkinson, Doença dept_BR
dc.titleThe Mini-BESTest is an independent predictor of falls in Parkinson diseasept_BR
dc.typeArtigo de Periódicopt_BR
dc.url.externahttps://www.sciencedirect.com/science/article/pii/S1413355518308098?via%3Dihub#!pt_BR
dc.identifier.orcidhttps://orcid.org/0000-0002-5968-2195pt_BR
dc.identifier.orcidhttp://orcid.org/0000-0003-4059-1645pt_BR
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