Impact of depression on gait variability in Parkinson’s disease

Dragašević-Mišković, Nataša; Bobić, Vladislava; Kostić, Milutin; Stanković, Iva; Radovanović, Saša; Dimitrijević, Kosta; Svetel, Marina; Petrović, Igor; Đurić-Jovičić, Milica

doi:10.1016/j.clineuro.2020.106324

Cited by 18 publications

(10 citation statements)

References 45 publications

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“…Based on findings from the current study, emotional states did not influence gait variability, nor postural control. Previous research showed that different mood disorders, namely increased anxiety in older adults with PD showed greater step-to-step variability [19] and depression was shown to impact swing time variability (although this exists in the pace domain according to the 5-factor model of gait) [12]. The sample in this study involved young healthy adults.…”

Section: Discussionmentioning

confidence: 96%

“…Whereas other emotional states such as sadness and fear feature a reduction in speed, stride length, and step count [8][9][10]. Much of this past work has focused on quantifying aspects of pace, rather than variability of gait even though recent research has emphasized the clinical relevance of gait variability [11,12]. Furthermore, it is also important to note that most of the previous studies used a sample of professional actors to quantify emotional differences in walking, which can bias or exaggerate effect size of the results given that skilled actors are highly trained to produce stereotyped expressions [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

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Emotional states affect walking performance

Homagain

Martens

2023

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Gait is a large component and indicator of health in both young and older adults. Many factors affect gait including age, disease, and even mood disorders such as anxiety and depression. Few studies have looked at the role of emotional states on gait behaviour. This study aimed to investigate the influence of emotional states on walking performance to understand whether an emotional state may be an important factor to consider when evaluating gait. Thirty-six young adults were recruited (23F, 13M) and performed a neutral baseline condition of walking which included six passes of walking across an 8m walkway (a total of 48m of walking). Participants then completed 6 pseudo-randomized emotional state induction conditions while immersive 360-degree videos were used to induce the following emotional state conditions: happiness, excitement, sadness, fear, and anger. Participants viewed the emotion elicitation videos using a virtual reality head-mounted display (HMD), then rated their emotional state using self-assessment manikins and performed 48m of walking (without the HMD) over a pressure sensor walkway. Results showed that participants walked with significantly reduced step length and gait speed during the sadness condition compared to the other emotion conditions and the neutral condition. Furthermore, participants adjusted the timing of their walking during the sadness condition and walked with significantly increased step, stance, and swing times compared to other emotion conditions, but not the neutral condition. Step time was significantly reduced during the conditions of excitement and fear compared to the neutral condition. Overall, these findings show that in young healthy adults, emotions may impact variety of gait parameters involving pace and rhythm, however have little influence on gait variability and postural control. These results indicate that perhaps the emotions of sadness and excitement should be taken into account as potential confounds for future gait analysis.

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Section: Discussionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Emotional states affect walking performance

Homagain

Martens

2023

Preprint

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“…53,54 Pharmacological interventions treating other PD symptoms, such as depression (eg, serotonergic drugs), or interventions targeting other neurotransmitter systems, such as the noradrenergic system, could provide prognostic insights as these have had some effects on freezing and mobility deficits in PD. [55][56][57][58] The model-based predictions were tested for their usefulness in clinical trial enrichment scenarios. Enriching trial enrollment for participants that are more likely to reach an endpoint of interest has been used in other neurodegenerative diseases.…”

Section: Discussionmentioning

confidence: 99%

Predicting Ambulatory Capacity in Parkinson's Disease to Analyze Progression, Biomarkers, and Trial Design

et al. 2023

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BackgroundIn Parkinson's disease (PD), gait and balance is impaired, relatively resistant to available treatment and associated with falls and disability. Predictive models of ambulatory progression could enhance understanding of gait/balance disturbances and aid in trial design.ObjectivesTo predict trajectories of ambulatory abilities from baseline clinical data in early PD, relate trajectories to clinical milestones, compare biomarkers, and evaluate trajectories for enrichment of clinical trials.MethodsData from two multicenter, longitudinal, observational studies were used for model training (Tracking Parkinson's, n = 1598) and external testing (Parkinson's Progression Markers Initiative, n = 407). Models were trained and validated to predict individuals as having a “Progressive” or “Stable” trajectory based on changes of ambulatory capacity scores from the Movement Disorders Society Unified Parkinson's Disease Rating Scale parts II and III. Survival analyses compared time‐to‐clinical milestones and trial outcomes between predicted trajectories.ResultsOn external evaluation, a support vector machine model predicted Progressive trajectories using baseline clinical data with an accuracy, weighted‐F1 (proportionally weighted harmonic mean of precision and sensitivity), and sensitivity/specificity of 0.735, 0.799, and 0.688/0.739, respectively. Over 4 years, the predicted Progressive trajectory was more likely to experience impaired balance, loss of independence, impaired function and cognition. Baseline dopamine transporter imaging and select biomarkers of neurodegeneration were significantly different between predicted trajectory groups. For an 18‐month, randomized (1:1) clinical trial, sample size savings up to 30% were possible when enrollment was enriched for the Progressive trajectory versus no enrichment.ConclusionsIt is possible to predict ambulatory abilities from clinical data that are associated with meaningful outcomes in people with early PD. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

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“…Finally, our study has limitations. While in part our findings could be attributed to depression which was shown to affect gait parameters, in particular swing time variability [ 27 ], we excluded patients with major depression, and, while depressive symptoms have worsened over follow up, overall Hamilton depression rating scale score remained well below proposed threshold for depression (5.02 ± 4.40 vs. 7.02 ± 5.85; p = 0.022). Additionally, we did not take into account weight changes nor level of exercise as potential factors that could had had some impact on our findings.…”

Section: Discussionmentioning

confidence: 99%

Gait alterations in Parkinson’s disease at the stage of hemiparkinsonism—A longitudinal study

et al. 2022

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Background Progressive gait impairment in Parkinson’s disease (PD) leads to significant disability. Quantitative gait parameters analysis provides valuable information about fine gait alterations. Objectives To analyse change of gait parameters in patients with early PD at the stage of hemiparkinsonism and after 1 year of follow up, taking into account clinical asymmetry. Methods Consecutive early PD outpatients with strictly unilateral motor features underwent clinical and neuropsychological assessment at the study entry and after 1 year of follow up. Gait was assessed with GAITRite walkway using dual-task methodology. Spatiotemporal gait parameters (step time and length, swing time and double support time) and their coefficients of variation (CV), gait velocity and heel-to-heel base support were evaluated. Results We included 42 PD patients with disease duration of 1.3 years (±1.13). Progression of motor and non-motor symptoms, without significant cognitive worsening, was observed after 1 year of follow up. Significant shortening of the swing time, prolongation of the double support and increase of their CVs were observed during all task conditions similarly for most parameters on symptomatic and asymptomatic bodysides, except for CV for the swing time under the combined task. Conclusion Alterations of the swing time and double support time are already present even at the asymptomatic body side, and progress similarly, or even at faster pace, at this side, despite dopaminergic treatment These parameters deserve further investigation in larger, prospective studies to address their potential to serve as markers of progression in interventional disease modifying trials with early PD patients.

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Impact of depression on gait variability in Parkinson’s disease

Cited by 18 publications

References 45 publications

Emotional states affect walking performance

Emotional states affect walking performance

Predicting Ambulatory Capacity in Parkinson's Disease to Analyze Progression, Biomarkers, and Trial Design

Gait alterations in Parkinson’s disease at the stage of hemiparkinsonism—A longitudinal study

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