Full length articleLongitudinal changes over thirty-six months in postural control dynamics and cognitive function in people with Parkinson's disease
Introduction
Parkinson’s disease (PD) is the second most common neurodegenerative disease with a worldwide prevalence greater than 1% in adults over 70 [1]. Early motor symptoms include rigidity, bradykinesia, tremor and gait impairment with postural instability emerging as the disease progresses [2]. Postural instability is a known predictor of falls with consequential impact on wellbeing [3]. Over 20% of people with PD have also been reported to have mild cognitive impairment (MCI) at initial diagnosis [4]. Changes in cognitive function are associated with postural instability [5,6] and with an increased risk of falls [7,8]. A neuroimaging study supports the link between cognitive function and falling in PD with reduced grey matter reported in the posterior caudate (associated with cognitive function) in fallers compared to fallers [8]. Management of postural instability is challenging as it is often resistant to dopaminergic therapy [9]. Nonpharmaceutical interventions include different treadmill training protocols which show limited improvements in gait and balance [10,11].
Clinically, assessment of postural instability is the Pull test, included in the Unified Parkinson’s Disease Rating Scale (UPDRS III), which is insensitive to small changes in postural stability [12]. Objectively, postural stability has been assessed through centre of pressure (COP) parameters recorded from a force platform [13] and more recently, from body-worn monitors such as accelerometers [[14], [15], [16]]. The derived postural parameters are generally linear, providing information about signal characteristics averaged across time. However, as postural stability is a function of postural control, parameters that reflect underlying neural control mechanisms may yield additional information. For example, people with PD have reduced automatic control and greater conscious control of posture [17,18]. This altered regulatory mechanism may present as a change in regularity or predictability of postural parameters.
The purpose of this study was to investigate predictability of postural trunk dynamics through nonlinear analysis of tri-axial accelerometer signals. We included vertical accelerometry data as postural control operates in three dimensions and changes in perception of the postural vertical in older adults have been postulated [19]. We compared postural trunk predictability in people with recently diagnosed PD to postural trunk predictability in healthy older adults (HOA). Additionally, we investigated changes in this parameter over a 36 month period and its relationship to cognitive dysfunction. We hypothesised that (1) Postural trunk predictability is different in people with PD due to the loss of automatic control; (2) Postural trunk predictability changes over time in people with PD, as a result of increasing loss of automatic motor behaviour; (3) Postural trunk predictability is correlated with clinical measures of cognitive dysfunction, reflecting common dysfunctional neural pathways. This analysis may offer information about the underlying postural control mechanisms, its application as an early biomarker and as an indicator of disease progression.
Section snippets
Study design
This study was approved by the Newcastle and North Tyneside Research Ethics Committee (project registration number 09/H0906/82). The study group consisted of 50 people (17 female) recently diagnosed with PD and 59 HOA (26 female), recruited as part of the Incidence of Cognitive Impairment in Cohorts with Longitudinal Evaluation-GAIT (ICICLE-GAIT) study conducted between June 2009 and December 2011. Postural and cognitive assessments were undertaken at approximately 18 months, 36 months and 54
Demographic and cognitive data
The age range of participants across the three time-periods was 44.9–92.0 years for the PD group and 53.7–90.8 years for the HOA. The PD group were significantly younger (F1,280 = 10.3, p = 0.001). There was a smaller proportion of females in the PD group compared to the HOA group (34% versus 44%), and they had a lower MoCA score (F1,280 = 7.3, p = 0.007) (Table 1).
Signal nonlinear characterization
Fig. 1 illustrates representative 20 s tri-axial accelerometer data for a person with Parkinson’s and a healthy older adult. The
Discussion
This study investigated three dimensional postural dynamics in people with PD and HOA over a 36 month period, through SampEn analysis of trunk accelerometry signals. Trunk acceleration is less predictable in people with PD when standing, suggesting less constrained regulation of posture is associated with reduced automatic control, confirming our first hypothesis. We did not observe any progression of postural movement unpredictability with time in the people with PD, contrary to our second
Conclusion
Sample entropy of postural acceleration provides a sensitive measure to distinguish people with PD from HOA. However, it does not monitor progression of PD. A novel finding is the association of postural control in the anteroposterior and vertical directions with cognitive function and mediolateral direction with motor function. Further studies will determine how these nonlinear parameters relate to underlying neural correlates and clinical function.
Conflicts of interest
None.
Acknowledgments
The ICICLE-GAIT study was supported by Parkinson’s UK (J-0802, G-1301) and by the NIHR Newcastle Biomedical Research Centre. Additional support was provided by the NIHR/Wellcome Trust Clinical Research Facility (CRF) infrastructure at Newcastle upon Tyne Hospitals NHS Foundation Trust and Newcastle University. The views expressed are those of the authors and not necessarily those of the NHS or NIHR or the Department of Health. The authors would like to thank Dr. Gordon Duncan together with Dr.
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