An examination of the fall risk classification model in short-term intensive inpatient rehabilitation for elderly patients with Parkinson’s disease

Abstract

Aim: To examine the predictive model that classifies the fluctuation in fall risk two weeks after an evaluation at the beginning of short-term intensive inpatient rehabilitation for elderly patients with Parkinson’s disease (PD). Methods: Of the patients with PD ≥65 years old who underwent intensive rehabilitation, 17 patients (mean age: 76.5±6.1 years old) who had a fall risk detected by the Timed “Up & Go” including a cognitive task (TUG-cognitive) were enrolled in this study. The patients were divided into two groups depending on the TUG-cognitive two weeks after starting intensive rehabilitation: reduced fall risk or residual fall risk. The differences in the evaluated items between the two groups were examined, and those items found to have significant differences were used as independent variables in the logistic regression analysis with the fluctuation in fall risk after two weeks as the dependent variable. Results: A logistic regression analysis revealed that the fast-walking speed was a factor affecting the fluctuation in fall risk. In addition, the incidence of residual fall risk was calculated from the logistic function, and the risk was determined to be high when the fast-walking speed was ≤0.84 m/sec. Conclusions: The predictive model consisted of the TUG-cognitive and fast-walking speed at the beginning of intensive rehabilitation; it was suggested that the fluctuation in fall risk after two weeks could be classified based on these findings. Improvement of the fast-walking speed is important for reducing the fall risk in elderly patients with PD.