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

Scherbaum, Raphael; Moewius, Andreas; Oppermann, Judith; Geritz, Johanna; Hansen, Clint; Gold, Ralf; Maetzler, Walter; Tönges, Lars

doi:10.1007/s00415-022-11257-x

Cited by 7 publications

(4 citation statements)

References 123 publications

(173 reference statements)

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“…The total FES-I ranges from 16 to 64, with higher values indicating more concerns about falling. FES-I total scores were categorized into three groups: low (16-19 points), moderate (20)(21)(22)(23)(24)(25)(26)(27), and high concerns about falling (28-64), according to previous works [40,41].…”

Section: Assessmentsmentioning

confidence: 99%

“…Findings from gait analysis can help to distinguish PD subtypes, predict the risk of falling and increase the sensitivity of classical clinical fall risk factors to discriminate fallers from Sensors 2023, 23, 1111 2 of 10 non-fallers in PD [18][19][20]. In addition, wearables can also detect changes in PD symptoms due to treatment adaptation and rehabilitation [21,22].…”

Section: Introductionmentioning

confidence: 99%

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Gait Characteristics Associated with Fear of Falling in Hospitalized People with Parkinson’s Disease

Uhlig

Prell

2023

Sensors

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Background: Fear of falling (FOF) is common in Parkinson’s disease (PD) and associated with distinct gait changes. Here, we aimed to answer, how quantitative gait assessment can improve our understanding of FOF-related gait in hospitalized geriatric patients with PD. Methods: In this cross-sectional study of 79 patients with advanced PD, FOF was assessed with the Falls Efficacy Scale International (FES-I), and spatiotemporal gait parameters were recorded with a mobile gait analysis system with inertial measurement units at each foot while normal walking. In addition, demographic parameters, disease-specific motor (MDS-revised version of the Unified Parkinson’s Disease Rating Scale, Hoehn & Yahr), and non-motor (Non-motor Symptoms Questionnaire, Montreal Cognitive Assessment) scores were assessed. Results: According to the FES-I, 22.5% reported low, 28.7% moderate, and 47.5% high concerns about falling. Most concerns were reported when walking on a slippery surface, on an uneven surface, or up or down a slope. In the final regression model, previous falls, more depressive symptoms, use of walking aids, presence of freezing of gait, and lower walking speed explained 42% of the FES-I variance. Conclusion: Our study suggests that FOF is closely related to gait changes in hospitalized PD patients. Therefore, FOF needs special attention in the rehabilitation of these patients, and targeting distinct gait parameters under varying walking conditions might be a promising part of a multimodal treatment program in PD patients with FOF. The effect of these targeted interventions should be investigated in future trials.

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Section: Assessmentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Gait Characteristics Associated with Fear of Falling in Hospitalized People with Parkinson’s Disease

Uhlig

Prell

2023

Sensors

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“…Early detection and timely treatment of motor fluctuations are expected to improve their possibilities to live a normal life or to stay in work and be effective in work for longer periods, with a serious impact on the patients’ quality of life and the health economics of the system [43, 44]. The detection of gait-related symptoms, such as freezing of gait and postural instability, are key components when we try to optimize pharmacological and nonpharmacological treatment in Parkinson’s disease [45]. These are symptoms that also have a strong effect on the quality of life.…”

Section: Timely Interventions For Early and Advanced Pdmentioning

confidence: 99%

A Paradigm Shift in the Management of Patients with Parkinson’s Disease

Tsamis,

Odin,

Antonini

et al. 2023

Neurodegener Dis

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Background: Technological evolution leads to the constant enhancement of monitoring systems and recording symptoms of diverse disorders. Summary: For Parkinson’s disease, wearable devices empowered with machine learning analysis are the main modules for objective measurements. Software and hardware improvements have led to the development of reliable systems that can detect symptoms accurately and be implicated in the follow-up and treatment decisions. Key Messages: Among many different devices developed so far, the most promising ones are those that can record symptoms from all extremities and the trunk, in the home environment during the activities of daily living, assess gait impairment accurately, and be suitable for a long-term follow-up of the patients. Such wearable systems pave the way for a paradigm shift in the management of patients with Parkinson’s disease.

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“…Since DT walking situations can be daily-relevant for individuals with PD, DT interventions have been evaluated over the past years- with promising results mainly from a multi-centered randomized controlled trial with 120 patients with PD ( Strouwen et al, 2017 ; Geroin et al, 2018 ; Strouwen et al, 2019 ). However, while gait speed was identified as consistently responsive (which is the most commonly used walking parameter in treatment efficacy studies focusing on walking impairment), there is still a gap of knowledge with regard to responsiveness to treatment of various spatio-temporal walking parameters ( Polhemus et al, 2021 ; Scherbaum et al, 2022 ). Hence, a “one-size-fits-all” treatment approach may not mirror the complexity of the disease adequately ( Ginis et al, 2017 ; Witt et al, 2017 ; Nonnekes and Nieuwboer, 2018 ; Serrao et al, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

Cognitive parameters can predict change of walking performance in advanced Parkinson’s disease – Chances and limits of early rehabilitation

Geritz

Welzel²,

Hansen³

et al. 2022

Front. Aging Neurosci.

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IntroductionLinks between cognition and walking performance in patients with Parkinson’s disease (PD), which both decline with disease progression, are well known. There is lack of knowledge regarding the predictive value of cognition for changes in walking performance after individualized therapy. The aim of this study is to identify relevant predictive cognitive and affective parameters, measurable in daily clinical routines, for change in quantitative walking performance after early geriatric rehabilitation.MethodsForty-seven acutely hospitalized patients with advanced PD were assessed at baseline (T1) and at the end (T2) of a 2-week early rehabilitative geriatric complex treatment (ERGCT). Global cognitive performance (Montreal Cognitive Assessment, MoCA), EF and divided attention (Trail Making Test B minus A, delta TMT), depressive symptoms, and fear of falling were assessed at T1. Change in walking performance was determined by the difference in quantitative walking parameters extracted from a sensor-based movement analysis over 20 m straight walking in single (ST, fast and normal pace) and dual task (DT, with secondary cognitive, respectively, motor task) conditions between T1 and T2. Bayesian regression (using Bayes Factor BF10) and multiple linear regression models were used to determine the association of non-motor characteristics for change in walking performance.ResultsUnder ST, there was moderate evidence (BF10 = 7.8, respectively, BF10 = 4.4) that lower performance in the ∆TMT at baseline is associated with lower reduction of step time asymmetry after treatment (R2adj = 0.26, p ≤ 0.008, respectively, R2adj = 0.18, p ≤ 0.009). Under DT walking-cognitive, there was strong evidence (BF10 = 29.9, respectively, BF10 = 27.9) that lower performance in the ∆TMT is associated with more reduced stride time and double limb support (R2adj = 0.62, p ≤ 0.002, respectively, R2adj = 0.51, p ≤ 0.009). There was moderate evidence (BF10 = 5.1) that a higher MoCA total score was associated with increased gait speed after treatment (R2adj = 0.30, p ≤ 0.02).DiscussionOur results indicate that the effect of ERGT on change in walking performance is limited for patients with deficits in EF and divided attention. However, these patients also seem to walk more cautiously after treatment in walking situations with additional cognitive demand. Therefore, future development of individualized treatment algorithms is required, which address individual needs of these vulnerable patients.

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

Cited by 7 publications

References 123 publications

Gait Characteristics Associated with Fear of Falling in Hospitalized People with Parkinson’s Disease

Gait Characteristics Associated with Fear of Falling in Hospitalized People with Parkinson’s Disease

A Paradigm Shift in the Management of Patients with Parkinson’s Disease

Cognitive parameters can predict change of walking performance in advanced Parkinson’s disease – Chances and limits of early rehabilitation

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