RESUMEN
BACKGROUND: Previous studies have established that increased Sample Entropy (SampEn) of cadence, a measure of non-linear variability, during dynamic cycling leads to greater improvements in motor function for individuals with Parkinson's disease (PD). However, there is significant variability in responses among individuals with PD due to symptoms and disease progression. OBJECTIVES: The aim of this study was to develop and test a paradigm for adapting a cycling exercise intervention using SampEn of cadence and rider effort to improve motor function. METHODS: Twenty-two participants were randomized into either patient-specific adaptive dynamic cycling (PSADC) or non-adaptive (NA) group. SampEn of cadence was calculated after each of the 12 sessions, and motor function was evaluated using the Kinesia test. Pearson's correlation coefficient was used to analyze the relationship between SampEn of cadence and motor function improvement. Multiple linear regression (MLR) was used to identify the strongest predictors of motor function improvement. RESULTS: Pearson's correlation coefficient revealed a significant correlation between SampEn of cadence and motor function improvements (R2 = -.545, P = .009), suggesting that higher SampEn of cadence led to greater motor function improvement. MLR demonstrated that SampEn of cadence was the strongest predictor of motor function improvement (ß = -8.923, t = -2.632, P = .018) over the BMI, Levodopa equivalent daily dose, and effort. CONCLUSIONS: The findings show that PSADC paradigm promoted a greater improvement in motor function than NA dynamic cycling. These data will be used to develop a predictive model to optimize motor function improvement after cycling in individuals with PD.
RESUMEN
Purpose: To evaluate how the changes in directly measured cardiorespiratory fitness (CRF) relate to the changes in metabolic syndrome (MetS) status following 4-6 months of exercise training. Methods: Maximal cardiopulmonary exercise (CPX) tests and MetS risk factors were analyzed prospectively from 336 adults (46% women) aged 45.8 ± 10.9 years. MetS was defined according to the National Cholesterol Education Program-Adult Treatment Panel III criteria, as updated by the American Heart Association/National Heart, Lung, and Blood Institute (AHA/NHLBI). Pearson correlations, chi-squares, and dependent 2-tail t-tests were used to assess the relationship between the change in CRF and the change in MetS risk factors, overall number of MetS risk factors, and a MetS severity score following 4-6 months of participation in a self-referred, community-based exercise program. Results: Overall prevalence of MetS decreased from 23% to 14% following the exercise program (P < 0.05), while CRF improved 15% (4.7 ± 8.4 mL/kg/min, P < 0.05). Following exercise training, the number of positive risk factors declined from 1.4 ± 1.3 to 1.2 ± 1.2 in the overall cohort (P < 0.05). The change in CRF was inversely related to the change in the overall number of MetS risk factors (r = -0.22; P < 0.05) and the MetS severity score (r = -0.28; p < 0.05). Conclusion: This observational cohort study indicates an inverse relationship between the change in CRF and the change in MetS severity following exercise training. These results suggest that participation in a community-based exercise program yields significant improvements in CRF, MetS risk factors, the prevalence of the binary MetS, and the MetS severity score. Improvement in CRF through exercise training should be a primary prevention strategy for MetS.