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

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dc.creatorLarissa Karlla Rodrigues Lopes
dc.creatorAline Alvim Scianni
dc.creatorLidiane Oliveira Lima
dc.creatorRaquel de Carvalho Lana
dc.creatorFatima Rodrigues de Paula
dc.date.accessioned2022-06-23T17:34:41Z
dc.date.accessioned2025-09-09T01:12:50Z
dc.date.available2022-06-23T17:34:41Z
dc.date.issued2020-09
dc.description.sponsorshipCNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico
dc.description.sponsorshipFAPEMIG - Fundação de Amparo à Pesquisa do Estado de Minas Gerais
dc.description.sponsorshipCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
dc.format.mimetypepdf
dc.identifier.doihttps://doi.org/10.1016/j.bjpt.2019.07.006
dc.identifier.issn1413-3555
dc.identifier.urihttps://hdl.handle.net/1843/42623
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofBrazilian Journal of Physical Therapy
dc.rightsAcesso Aberto
dc.subjectFisioterapia
dc.subjectAcidentes por quedas
dc.subjectFatores de risco
dc.subjectParkinson, Doença de
dc.subject.otherPhysical therapy
dc.subject.otherAccidental falls
dc.subject.otherRisk factors
dc.titleThe Mini-BESTest is an independent predictor of falls in Parkinson disease
dc.typeArtigo de periódico
local.citation.epage440
local.citation.issue5
local.citation.spage433
local.citation.volume24
local.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.
local.identifier.orcidhttps://orcid.org/0000-0002-5968-2195
local.identifier.orcidhttp://orcid.org/0000-0003-4059-1645
local.publisher.countryBrasil
local.publisher.departmentEEF - DEPARTAMENTO DE FISIOTERAPIA
local.publisher.initialsUFMG
local.url.externahttps://www.sciencedirect.com/science/article/pii/S1413355518308098?via%3Dihub#!

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