Perturbation training is a promising approach to reduce fall incidence in persons with Parkinson disease (PwPD). This study aimed to evaluate interindividual differences in balance adaptations in response to perturbation treadmill training (PTT) and identify potential outcome predictors.
PwPD (n = 43, Hoehn & Yahr stage 1-3.5) were randomly assigned to either 8 weeks of PTT or conventional treadmill training (CTT) without perturbations. At baseline and following intervention, data from 4 domains of balance function (reactive, anticipatory, dynamic postural control, and quiet stance) were collected. Using responder analysis we investigated interindividual differences (responder rates and magnitude of change) and potential predictive factors.
PTT showed a significantly higher responder rate in the Mini Balance Evaluation Systems Test (Mini-BESTest) subscore reactive postural control, compared with CTT (PTT = 44%; CTT = 10%; risk ratio = 4.22, confidence interval = 1.03-17.28). Additionally, while between-groups differences were not significant, the proportion of responders in the measures of dynamic postural control was higher for PTT compared with CTT (PTT: 22%-39%; CTT: 5%-10%). The magnitude of change in responders and nonresponders was similar in both groups. PTT responders showed significantly lower initial balance performance (4/8 measures) and cognitive function (3/8 measures), and were older and at a more advanced disease stage, based on descriptive evaluation.
Our findings suggest that PTT is beneficial to improve reactive balance in PwPD. Further, PTT appeared to be effective only for a part of PwPD, especially for those with lower balance and cognitive function, which needs further attention.
Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1, http://links.lww.com/JNPT/A1).
Department of Sport Science and Sport, Friedrich-Alexander-University (FAU) Erlangen-Nürnberg, Erlangen, Germany (S.K., K.P., S.S.); Molecular Neurology, University Hospital Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany (H.G., J.W., J.K.); and Machine Learning and Data Analytics Lab, FAU Erlangen-Nürnberg, Erlangen, Germany (B.E.).
Correspondence: Sarah Klamroth, MA, Department of Sport Science and Sport, Friedrich-Alexander-University Erlangen-Nürnberg, Gebbertstrasse 123b, 91058 Erlangen, Germany (email@example.com).
The study was supported by the Emerging Fields Initiative of the Friedrich-Alexander-University Erlangen-Nürnberg (FAU, Germany) and the German Foundation Neurology (Deutsche Stiftung Neurologie).
The article reflects work that has been presented previously as a poster at the annual conference of the German Society for Physical Therapy Research (Deutsche Gesellschaft für Physiotherapie Wissenschaft, DGPTW) in November 2018 in Lübeck, Germany.
Study sponsors were not involved in the study design, in the collection, in the analysis, in the interpretation of data, in the writing of the manuscript, and in the decision to submit the manuscript for publication.
The authors declare no conflicts of interest with respect to the research, authorship, and/or publication of this article.
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