Preditores de quedas na doença de Parkinson: dados do estudoRede Parkinson Brasil - REPARK - BR

• Ano de defesa: 2018
• Autor(a) principal: Larissa Karlla Rodrigues Lopes
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais; UFMG
• Palavras-chave em Português: Doença de Parkinson; Equilíbrio postural; Quedas acidentais; Fatores de risco; Acidentes por quedas; Parkinson, Doença de
• Link de acesso: http://hdl.handle.net/1843/BUBD-BATHNB

Falls in Parkinson Disease (PD) are a complex health problem, with multidimensional causes and consequences, having a high occurrence rate in this population. Recurrent falls increase the physical, social and financial burden of the disease and the chances of hospitalization and institutionalization, generatingfear of further falls, limitations in activities of daily living, leading to the adoption of a sedentary lifestyle. In a population that tends to grow, falls in PD can have an even greater impact on health systems around the world.Thus, the demands related to the predictive factorsneeds to be highlighted. This is the first cross-sectional multicenter study conducted with a sample of PD individuals representative of the Brazilian population from different regions of the country. The aims of the present study were identify the main fall predictors in individuals with Parkinsons disease and compare fallers and non-fallers in relation to their socio-demographic, anthropometric, clinical and functional status. Data collected included: age, sex, BMI, PD progression, levodopa dosage, disease commitment (UPDRS ADL/Motor/Total), level of physical activity (HAP-AAS), fear of falls (FES-I), freezing of gait (FOG-Q), gait speed (10-MWT), lower limb functional strength (FTSST), balance (Mini-BESTest total and the domains), mobility (TUG) and dual-task dynamic (TUG-DT). Participants that presented 1 fall in the last 12 months were classified as non-fallers and with 2 falls classified as fallers.Seventeen potential predictors were identified. Logistic regression analysis and ROC curve were applied. A total of 370 individuals, 44.87% fallers and 55.13% non-fallers participated in the study. Mann-Whitney U test showed that fallers presented worse performance in: UPDRS motor/ADL /Total, FES-I and FOG-Q (p <0.001); TUG (p = 0.005) and TUG-DT (p = 0.003); Mini-BESTest total and separate domains (p <0.001) and HAP (p <0.001), and were in their majority inactive or moderately active. The Mini-BESTest Total was the main independent predictor of falls in PD (OR = 0.92; p <0.001; 95% CI = 0.89 to 0.95). For each unit of increase in the Mini-BESTest there is an average reduction of 8% in the probability of being a faller. A cut-off point in the Mini-BESTest of 21.5/28 (AUC= 0.669, sensitivity 70.7% and specificity 55.1%) was established. The understanding of the sociodemographic, clinical, functional and anthropometric characteristics of fallers and non-fallers with PD, together with an instrument with excellentmeasurement propertiesthat identify PD with and without risk of falls,allows the development of specific interventions with satisfactory results.