Department of Physical Therapy, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil.
Department of Physical Therapy, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil.
Braz J Phys Ther. 2020 Sep-Oct;24(5):433-440. doi: 10.1016/j.bjpt.2019.07.006. Epub 2019 Jul 25.
Falls in Parkinson Disease (PD) are a complex health problem, with multidimensional causes and consequences.
To identify the fall predictors in individuals with PD and compare fallers and non-fallers considering their socio-demographic, anthropometric, clinical and functional status.
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.
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.
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.
帕金森病（PD）患者的跌倒问题是一个复杂的健康问题，其具有多维度的病因和后果。
确定 PD 患者的跌倒预测因素，并比较跌倒者和非跌倒者，同时考虑他们的社会人口统计学、人体测量学、临床和功能状况。
采用多中心横断面设计。研究变量包括：年龄、性别、体重指数、PD 进展、左旋多巴剂量、活动受限和运动障碍（UPDRS 日常生活活动/运动）、身体活动水平（人体活动概况 - HAP）、对跌倒的恐惧（跌倒效能量表 - 国际版 - FES-I）、冻结步态（冻结步态问卷 - FOG-Q）、步态速度（10 米步行测试 - 10-MWT）、下肢功能力量（五次坐立试验 - FTSST）、平衡（Mini-BESTest）、移动能力（计时“站起行走”测试 - TUG）和双重任务动态测试（TUG-DT）。确定了 17 个潜在预测因素。采用逻辑回归和 ROC 曲线进行分析。
共有 370 名患者（44.87%的跌倒者和 55.13%的非跌倒者）完成了研究。跌倒者在 UPDRS 运动/ADL/总分、FES-I、FOG-Q、Mini-BESTest、HAP、TUG 和 TUG-DT 中的表现更差，且大多数人活动量不足。Mini-BESTest 总分是跌倒的主要独立预测因素（OR=0.92；p<0.001；95%CI=0.89, 0.95）。Mini-BESTest 每增加一个单位，跌倒的可能性平均降低 8%。确定了 21.5/28 的截断点（AUC=0.669，敏感性 70.7%，特异性 55.1%）。
除了对跌倒者和非跌倒者进行特征描述和比较外，本研究还表明，Mini-BESTest 是 PD 患者跌倒的最强个体预测因素，强调了在跌倒风险评估中评估动态平衡能力的重要性。
