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Background: Gait impairments are characteristic motor manifestations and significant predictors of poor quality of life in Parkinson's disease (PD). Neuroimaging biomarkers for gait impairments in PD could facilitate effective interventions to improve these symptoms and are highly warranted., Objective: The aim of this study was to identify neural networks of discrete gait impairments in PD., Methods: Fifty-five participants with early-stage PD and 20 age-matched healthy volunteers underwent quantitative gait assessment deriving 12 discrete spatiotemporal gait characteristics and [ 18 F]-2-fluoro-2-deoxyglucose-positron emission tomography measuring resting cerebral glucose metabolism. A multivariate spatial covariance approach was used to identify metabolic brain networks that were related to discrete gait characteristics in PD., Results: In PD, we identified two metabolic gait-related covariance networks. The first correlated with mean step velocity and mean step length (pace gait network), which involved relatively increased and decreased metabolism in frontal cortices, including the dorsolateral prefrontal and orbital frontal, insula, supplementary motor area, ventrolateral thalamus, cerebellum, and cuneus. The second correlated with swing time variability and step time variability (temporal variability gait network), which included relatively increased and decreased metabolism in sensorimotor, superior parietal cortex, basal ganglia, insula, hippocampus, red nucleus, and mediodorsal thalamus. Expression of both networks was significantly elevated in participants with PD relative to healthy volunteers and were not related to levodopa dosage or motor severity., Conclusions: We have identified two novel gait-related brain networks of altered glucose metabolism at rest. These gait networks could serve as a potential neuroimaging biomarker of gait impairments in PD and facilitate development of therapeutic strategies for these disabling symptoms. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society., (© 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.)

Background: Gait disturbance is an early, disabling feature of Parkinson's disease (PD) that is typically refractory to dopaminergic medication. The cortical cholinergic system, originating in the nucleus basalis of Meynert of the basal forebrain, has been implicated. However, it is not known if degeneration in this region relates to a worsening of disease-specific gait impairment., Objective: To evaluate associations between sub-regional cholinergic basal forebrain volumes and longitudinal progression of gait impairment in PD., Methods: 99 PD participants and 47 control participants completed gait assessments via an instrumented walkway during 2 minutes of continuous walking, at baseline and for up to 3 years, from which 16 spatiotemporal characteristics were derived. Sub-regional cholinergic basal forebrain volumes were measured at baseline via MRI and a regional map derived from post-mortem histology. Univariate analyses evaluated cross-sectional associations between sub-regional volumes and gait. Linear mixed-effects models assessed whether volumes predicted longitudinal gait changes., Results: There were no cross-sectional, age-independent relationships between sub-regional volumes and gait. However, nucleus basalis of Meynert volumes predicted longitudinal gait changes unique to PD. Specifically, smaller nucleus basalis of Meynert volume predicted increasing step time variability (P = 0.019) and shortening swing time (P = 0.015); smaller posterior nucleus portions predicted shortening step length (P = 0.007) and increasing step time variability (P = 0.041)., Conclusions: This is the first study to demonstrate that degeneration of the cortical cholinergic system predicts longitudinal progression of gait impairments in PD. Measures of this degeneration may therefore provide a novel biomarker for identifying future mobility loss and falls. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society., (© 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.)

Falls are a major determinant of poor quality of life, immobilization, and reduced life expectancy in people affected by Parkinson's disease (PD) and in older adults more generally. Although many questions remain, recent research has advanced the understanding of this complex problem. The goal of this review is to condense new knowledge of falls in PD from prodromal to advanced disease, taking into account risk factors, assessment, and classification as well as treatment. The fundamental steps of clinical and research-based approaches to falls are described, namely, the identification of fall risk factors, clinical and instrumental methods to evaluate and classify fall risk, and the latest evidence to reduce or delay falls in PD. We summarize recent developments, the direction in which the field should be heading, and what can be recommended at this stage. We also provide a practical algorithm for clinicians.© 2017 International Parkinson and Movement Disorder Society., (© 2017 International Parkinson and Movement Disorder Society.)

Background: Falls are common and associated with reduced independence and mortality in Parkinson's disease. Previous research has been conducted on falls-prevalent or advanced disease cohorts., Objective: This study identifies risk factors for first fall for 36 months in a newly diagnosed, falls-naïve cohort., Methods: A total of 121 consecutive Parkinson's disease patients were recruited. Falls data were collected prospectively during 36 months from diagnosis via monthly falls diaries and telephone follow-up for 117 participants. Assessment comprised a comprehensive battery of clinical, gait, and cognitive measures. Significant predictors were identified from decision-tree analysis and survival analysis with time to first fall during 36 months as the dependent variable., Findings: At baseline, 26 (22%) participants reported retrospective falls. At 36 months, the remaining cohort (n = 91) comprised 47 fallers (52%) and 30 (33%) nonfallers and 14 (15%) participants with incomplete diaries. Fallers presented with a significantly higher disease severity, poorer ability to stand on one leg, slower gait speed, increased stance time variability, and higher swing time asymmetry. Median time to first fall was 847 days. Gait speed, stance time, and Hoehn & Yahr III stage emerged as significant predictors of first fall, hazard ratio 3.44 (95% confidence interval [CI] 1.58 to 7.48), 3.31(95% CI 1.40 to 7.80), and 2.80 (95% CI 1.38 to 5.65), respectively. The hazard ratio for risk factors combined was 7.82 (CI 2.80 to 21.84)., Conclusions: Interventions that target gait deficit and postural control in early Parkinson's disease may limit the potential for first fall. © 2016 International Parkinson and Movement Disorder Society., (© 2016 International Parkinson and Movement Disorder Society.)

Wearable technology comprises miniaturized sensors (eg, accelerometers) worn on the body and/or paired with mobile devices (eg, smart phones) allowing continuous patient monitoring in unsupervised, habitual environments (termed free-living). Wearable technologies are revolutionizing approaches to health care as a result of their utility, accessibility, and affordability. They are positioned to transform Parkinson's disease (PD) management through the provision of individualized, comprehensive, and representative data. This is particularly relevant in PD where symptoms are often triggered by task and free-living environmental challenges that cannot be replicated with sufficient veracity elsewhere. This review concerns use of wearable technology in free-living environments for people with PD. It outlines the potential advantages of wearable technologies and evidence for these to accurately detect and measure clinically relevant features including motor symptoms, falls risk, freezing of gait, gait, functional mobility, and physical activity. Technological limitations and challenges are highlighted, and advances concerning broader aspects are discussed. Recommendations to overcome key challenges are made. To date there is no fully validated system to monitor clinical features or activities in free-living environments. Robust accuracy and validity metrics for some features have been reported, and wearable technology may be used in these cases with a degree of confidence. Utility and acceptability appears reasonable, although testing has largely been informal. Key recommendations include adopting a multidisciplinary approach for standardizing definitions, protocols, and outcomes. Robust validation of developed algorithms and sensor-based metrics is required along with testing of utility. These advances are required before widespread clinical adoption of wearable technology can be realized. © 2016 International Parkinson and Movement Disorder Society., (© 2016 International Parkinson and Movement Disorder Society.)

Gait impairment in Parkinson's disease (PD) persists despite the use of dopaminergic therapy. Motor phenotype associated with greater postural instability and gait difficulty is related to a greater risk of motor decline and may be influenced by non-dopaminergic pathology. This study documents the progression of gait impairment over 18 months in an incident cohort of PD with regard to phenotype and medication. Gait characteristics were measured in 121 PD and 184 controls, and 18 months later in 108 PD participants. Sixteen gait characteristics were examined with respect to five broad domains for PD and motor phenotype. Correlations between change in levodopa (l-dopa) equivalent daily dose and gait were used to identify dopa-responsive and nonresponsive characteristics. Pace and rhythm deteriorated over 18 months in people with PD, with other gait domains remaining stable. People with a postural instability and gait difficulty phenotype had more impaired gait at baseline compared with a tremor-dominant phenotype, which was most evident in temporal characteristics. In contrast, pace and variability deteriorated over the subsequent 18 months in the tremor-dominant phenotype only. Weak but statistically significant correlations were found between increased l-dopa medication and less deterioration in pace and asymmetry. Significant gait impairment is evident in very early disease despite optimal medication. Change over 18 months is subtle and discrete, and is more pronounced in the tremor-dominant phenotype. Some features of gait are refractory to dopaminergic therapy, implicating a non-dopaminergic contribution. This may explain more temporal gait disturbance in the postural instability and gait difficulty phenotype., (© 2014 International Parkinson and Movement Disorder Society.)

Background: Spinocerebellar ataxia type 6 (SCA6) is an inherited ataxia with no established treatment. Gait ataxia is a prominent feature causing substantial disability. Understanding the evolution of the gait disturbance is a key step in developing treatment strategies., Methods: We studied 9 gait variables in 24 SCA6 (6 presymptomatic; 18 symptomatic) and 24 controls and correlated gait with clinical severity (presymptomatic and symptomatic)., Results: Discrete gait characteristics precede symptoms in SCA6 with significantly increased variability of step width and step time, whereas a more global gait deficit was evident in symptomatic individuals. Gait characteristics discriminated between presymptomatic and symptomatic individuals and were selectively associated with disease severity., Conclusions: This is the largest study to include a detailed characterization of gait in SCA6, including presymptomatic subjects, allowing changes across the disease spectrum to be compared. Selective gait disturbance is already present in SCA6 before clinical symptoms appear and gait characteristics are also sensitive to disease progression. Early gait disturbance likely reflects primary pathology distinct from secondary changes. These findings open the opportunity for early evaluation and sensitive measures of therapeutic efficacy using instrumented gait analysis which may have broader relevance for all degenerative ataxias., (© 2013 Movement Disorder Society.)

Gait is emerging as a powerful measurement tool in neurodegenerative disorders to identify markers of incipient pathology, inform diagnostic algorithms and disease progression, and measure the efficacy of interventions. However, it is unclear which of the many gait outcomes is most appropriate for each of these purposes. In this review, we summarise key topics relating to gait measurement. We draw on literature from Parkinson's disease, ageing, and neurodegenerative disease to address the issue of variable selection with the goal of moving toward a structured approach to measurement. Findings from this review identify a wide range of spatiotemporal and dynamic characteristics; however, their suitability differs according to the aim of measurement. Gait speed is useful as a global characteristic of performance but may not capture the nature of underlying pathology. Inconsistent application, reporting, and interpretation of gait outcomes currently preclude a prescriptive approach. Conceptual models of gait may facilitate a reasoned approach to outcome selection. We also recommend harmonisation of protocols, longitudinal cohort studies, and use of novel technologies and methods of analysis to provide a complete picture of gait. Gait characteristics are "fit for purpose" when selected according to a clear rationale and in accordance with their clinimetric properties. Evidence supports the use of gait as a biomarker of disease and to complement diagnosis and inform disease management. A structured approach to measurement is urgently required to fully realise the contribution gait can make to our understanding of neurodegenerative disease., (© 2013 Movement Disorder Society.)

The association between nonmotor characteristics and gait in Parkinson's disease (PD) is well established, particularly the role of cognition. Evidence is emerging that depression, an underrecognized symptom in PD is also associated with gait impairment. This cross-sectional study examined the association between depressive symptomatology and gait in early PD. Depression was measured with the Geriatric Depression Scale (GDS), disease severity with the Unified Parkinson's Disease Rating Scale III, and cognition with the Mini Mental Status Examination. Gait speed and gait variability were measured using a 7-m walkway (GAITRite). Linear regression was used to examine the association between depression and gait for PD and controls, controlling for age, cognition, and severity. PD participants who presented with clinically relevant depressive symptoms (GDS ≥ 5) were compared with those who scored < 5. One hundred and twenty-two people with newly diagnosed PD and 184 controls were assessed. Depression scores were significantly higher for PD patients than for controls (P < .001), although neither group presented with clinically relevant symptomatology (mean [SD] for PD, 2.7 [2.3]; for controls, 1.1 [1.8]). For gait speed there was a main effect for depression (P < .001) and a group × depression interaction that approached significance (P = .054). For gait variability there was a main effect for depression (P < .01). PD participants with GDS scores ≥ 5 had a slower and more variable gait. Very mild depressive symptoms are associated with gait disturbance in early PD. Depression may be a marker for degeneration in nondopaminergic systems in early PD and influence mechanisms of gait disturbance. © 2013 Movement Disorder Society., (Copyright © 2012 Movement Disorder Society.)