Variability in Functional Improvements After Dynamic Cycling in Parkinson’s disease: 813 Board #209 May 27, 3

Previous studies in our lab have shown that dynamic cycling for three sessions over a single week resulted in a 13.9% reduction in motor symptoms of Parkinson’s disease (PD) as measured with the Unified Parkinson’s Disease Rating Scale part III motor score (UPDRS III). Despite these results, variability in individual responses to dynamic cycling was still present. Furthermore, variability in severity and progression of Parkinson’s disease symptoms with time makes it challenging to design therapy interventions that provide maximal benefits over the long term. PURPOSE:The aim of this study was to examine the variability in exercise parameters and motor function after dynamic and static cycling to gain insight into the biomechanical and physiological features that promote functional improvements. METHODS: Individuals with mild to moderate PD (N= 47) were randomly assigned into either a static or dynamic cycling group. Each subject was evaluated for changes in motor function before and after three exercise sessions. Features of exercise (power, cadence) and changes in motor function (UPDRS, Timed up and Go) were analyzed using variability analysis techniques (Sample Entropy) and independent t-tests. RESULTS:Variability analysis revealed that pattern irregularity in power was less in the dynamic group (0.22 ± .14) compared to the static group (0.44 ± .35, t= -8.7, =2.9, p= 0.005). In contrast, cadence data showed greater variability for the dynamic group (1.13 ± .32) than for the static group (.41 ± .22, t= -8.7, =2.9, p< 0.001). UPDRS III scores were significantly improved (t= 2.4, p= 0.018) after dynamic cycling (4.2 ± 7.0 pts) compared to static cycling (0.4 ± 5.6 pts), but there was greater variability in scores in the dynamic group. Timed up and go scores improved after dynamic cycling (-2.1 ± 6.0 secs) and worsened after static cycling (+2.0 ± 14.2 secs), but the difference was not significant due to variability in responses among subjects (t= -1.3, p= 0.198). CONCLUSIONS:These findings suggest that exercise interventions in PD are not “one size fits all” and support the idea that interventions need to be optimized for each individual. Variability analysis provides a unique method of examining individual responses to exercise as well as understanding how individual exercise characteristics could optimize motor function in Parkinson’s disease.