Kinematic and Clinical Outcomes to Evaluate the Efficacy of a Multidisciplinary Intervention on Functional Mobility in Parkinson's Disease

Abstract

Introduction: Functional mobility (FM) is a concept that incorporates the capacity of a person to move independently and safely to accomplish tasks. It has been proposed as a Parkinson's disease (PD) functional and global health outcome. In this study, we aimed to identify which kinematic and clinical outcomes changes better predict FM changes when PD patients are submitted to a specialized multidisciplinary program.Methods: PD patients engaged in a pre-defined specialized multidisciplinary program were assessed at admission and discharge. Change from baseline was calculated for all kinematic and clinical outcomes, and Timed Up and Go (TUG) was defined as the primary outcome for FM. A stepwise multivariate linear regression was performed to identify which outcome measures better predict TUG changes.Results: Twenty-four patients were included in the study. The changes in TUG Cognitive test, supervised step length, and free-living (FL) step time asymmetry were identified as the best predictors of TUG changes. The supervised step length and FL step time asymmetry were able to detect a small to moderate effect of the intervention (d values ranging from −0.26 to 0.42).Conclusions: Our results support the use of kinematic outcome measures to evaluate the efficacy of multidisciplinary interventions on PD FM. The TUG Cognitive, step length, and FL step time asymmetry were identified as having the ability to predict TUG changes. More studies are needed to identify the minimal clinically important difference for step length and FL step time asymmetry in response to a multidisciplinary intervention for PD FM.

Parkinson’s disease multimodal complex treatment improves gait performance: an exploratory wearable digital device-supported study

“…Possibly, the amplitude-oriented treatments during PD-MCT, i.e., LSVT-BIG exercises [61] additionally contribute to effects on stride length. Similar favorable effects of inpatient multidisciplinary interventions on gait parameters have been reported in observational [99,102] and controlled [103] studies. They likewise demonstrated improvements of gait velocity [99,102,103] and stride [103] or step [102] length measured by wearable digital devices [102], optoelectronic systems [103], and stopwatches [99] after more [102] or similarly intense [99,103] interventions with different [102,103] or similar [99] durations.…”

“…Evidence suggests that enhanced executive functions can be associated with dopaminergic [ 105 ] and exercise-related [ 106 , 107 ] effects, might contribute to improvements in gait [ 108 ] and balance [ 109 ], and are, therefore, favorable for daily functioning and quality of life [ 110 ]. Interestingly, an observational study [ 102 ] showed that changes in supervised step length and in dual-task walking abilities under supervised conditions best-predicted changes in functional mobility after a more intense inpatient multidisciplinary intervention [ 102 ]. Crucially, whatever the reasons are for the lack of significant improvement in gait speed and stride length during single-task walking, we argue that the improvement of gait under dual-task conditions is particularly relevant to daily life [ 85 ] and may enhance mobility and quality of life.…”

“…The small sample size may have also led to large confidence intervals of the exploratory Spearman correlation coefficients, which warrants a confirmatory breakdown of these results in future analyses. Another point is the supervised assessment condition in the inpatient setting where capacity [ 10 ] rather than usual real-life performance [ 10 ] is measured due to psychological aspects including social desirability and the Hawthorne effect [ 92 , 102 ]. A continuous assessment of self-initiated movements in daily life following PD-MCT would have been useful as PD patients walk differently, i.e., slower with shorter strides, in an unsupervised environment [ 122 , 123 ].…”

Personalised Gait Recognition for People with Neurological Conditions

“…A first challenge in gait analysis in free-living environments is that of automatically identifying gait (and non-gait) instances [ 3 ]. Recognising gait in free-living environments enables the calculation of macro and micro features—e.g., step variability and asymmetry [ 4 , 5 ]. The impact of classifying gait in free-living environments is severe to these endpoints, as the misclassification of a set of windows is likely to have a large effect on those micro characteristics and their interpretation [ 6 ].…”

Wild by Design: Workshop on Designing Ubiquitous Health Monitoring Technologies for Challenging Environments

“…This change of paradigm promises fine-grained monitoring of chronic and neurodegenerative diseases, early prediction of health conditions, accessible self-management, and the enablement of more effective personalised interventions. Recent research shows us the potential of these ubiquitous technologies: with body-worn accelerometer sensors, it is possible to monitor disease fluctuations in free-living environments [1,2,6,17]; predict hospital readmission [11]; monitor depression via social media posts [5]; detect continuous exposure to stress with wrist-worn devices [7]; use smartphones to passively monitor diseases [9,16] or perform rapid tests in low-resource settings [15]; among many others.…”