Parkinson's disease (PD) is a neurodegenerative disorder mainly classified by gait deficits such as bradykinesia, rigidity and tremor. However, people with PD ...
Predicting Cognitive Decline Using Gait Analysis in PD Morris R, Lord S and Rochester L.
Background Parkinson’s disease (PD) is a neurodegenerative disorder mainly classified by gait deficits such as bradykinesia, rigidity and tremor. However, people with PD also experience cognitive decline which can lead to PD dementia (PDD) with an incidence as high as 75%1. Dementia results in loss of independence, decreased quality of life and premature death. Therefore, the ability to detect people with PD at risk of cognitive decline and dementia is very important to patients, family and the NHS. Discrete gait characteristics can predict cognitive decline in healthy older adults2 but has yet to be replicated in PD. Such gait characteristics can now be measured both in the lab and at home by using portable monitors. Falls, another cause of reduced quality of life3, are experienced by ~40-70% of those with PD4 and are also related to both a deficit of gait5 and cognition6 in PD. This longitudinal study aims to identify gait variables that predict cognitive decline in incident PD in order to enhance management of PD. Secondary aims include analysis of gait, activity and falls and how these features change over time.
Methods
Falls
• ICICLE Gait is a longitudinal study observing the transition from PD to PDD
• Falls are a common cause of decreased mobility, reduced independence and reduced quality of life3
by assessing gait, balance and falls
• Falls diaries are kept by participants giving details of their falls each month,
• Participants include PD (n=121) and Healthy Controls (n=184) • Gait measurement methods include Vicon, GaitRite (Figure 1) and Axivity
including; • Where and when the fall occurred
Monitors (Figure 3)
• What caused the fall
• Cognitive tests include MMSE, MOCA, CDR, CANTAB
• How the participant recovered from the fall • Information from recurrent fallers can be matched to data from gait analysis and cognitive analysis • This data will allow us to define types of fallers and reasons for falls • Therefore can input treatment early to prevent reduced QOL
Figure 1: Image taken from GaitRite.
A
Measuring Gait in the Home • Measured using an Axivity monitor (Figure 2) • Patients wear for 7 days following testing • Allows us to measure activity in the community environment • The monitor supplies a signal and an amount of time that relates to lying
B
down, sitting or standing or walking (Figure 3B) • Looking more closely at the data provides information on the individual Figure 3. Axivity Measurements.
strides the participant makes (Figure 3A)
References 1. Aarsland, D & Kurz, MW. The Epidemiology of Dementia Associated with Parkinson’s Disease. (2010). Brain Pathology. 20 (3), pp. 633-639 2. Verghese, J et al. Quantitative Gait Dysfunction and Risk of Cognitive Decline and Dementia. (2007). Journal of Neurology, Neurosurgery and Psychiatry. 78 (9), pp. 929-935 3. Bloem BR et al. Prospective Assessment of Falls in Parkinson’s Disease. (2001). Journal of Neurology. 28 (11), pp. 950-958 4. Pickering, RM et al. A Meta-Analysis of Six Prospective Studies of Falling in Parkinson’s Disease. (2007). Movement Disorders. 22 (13), pp. 1892-1900 5. Hiorth, YH et al. Frequencies of Falls and Associated Features of Different Stages of Parkinson’s Disease. (2013). European Journal of Neurology. 20 (1), pp. 160-166 6. Holtzer, R et al. The Relationship between Specific Cognitive Functions and Falls in Aging. (2007). Neuropsychology. 21 (5), pp. 540-548
Figure 2. Axivity Monitor.
Presented at the Therapy Services Conference, 27th February 2014
