by Dr Christopher Kobylecki
Assessment of people with Parkinson’s is complex for several reasons. Each person has an individual symptom profile and disease trajectory, and we are only starting to understand what makes some people progress at a different rate than others. The pattern and impact of motor fluctuations and dyskinesia varies from person to person, and it can be challenging to determine the extent of motor as opposed to non-motor fluctuations. “Personalised medicine” is therefore an unmet aspiration for most people with Parkinson’s.
Assessment of these symptoms in the clinic is an imperfect tool for several reasons. Firstly, it only provides a “snap shot” for a short period of time, and one point on the trajectory of fluctuations people can experience. Secondly, assessment of gait and functional tasks is not as relevant as possible to the person’s home environment when performed in clinic. Thirdly, the stress associated with clinic visits may alter the results of assessment.
There is increasing interest in technological strategies to assess, monitor and manage people with Parkinson’s. These have developed from complicated systems to measure movement in a laboratory environment, to wearable devices, which monitor a variety of motor and non-motor features in the home of someone with Parkinson’s over a much longer time period than can be achieved from a clinic visit or ward admission. When we think about a device to monitor aspects of Parkinson’s, we want to be sure that it is going to be useful for our practice and help our patients. A recent paper from the Movement Disorder Society outlined four key points which we should expect from such technologies (1):
- They should provide accurate and clinically relevant results.
- They should contribute to a meaningful measure in terms of management, for example health-related quality of life (HRQoL).
- They should provide a target to allow one to assess whether a treatment or other intervention has worked.
- Repeatable and easy to use – to allow practical clinical use and “before and after” assessment of treatment effects.
Parkinson’s management is challenging precisely because of the variety of different symptoms, but recent developments in wearable monitoring systems for Parkinson’s have focused on the following:
- Bradykinesia and “off” time. Motor fluctuations, including wearing-off, occur in up to 50% of patients after five years of diagnosis and impact on HRQoL. Compliance with complicated medicine regimens is often poor. There is now evidence for a wearable monitoring system for assessment of bradykinesia and “off” time, which is repeatable and so can be used to assess treatment effects (2). The measurements generated by this tool can be used as part of the multidisciplinary assessment for consideration of non-oral therapies in Parkinson’s.
- Dyskinesia often occurs in combination with motor fluctuations and also impacts on HRQoL. The pressure of clinic assessments often impacts on dyskinesia assessment, so accurate evaluation of dyskinesia in the home environment is a priority.
- Non-motor symptoms. The plethora of non-motor symptoms in Parkinson’s makes assessment challenging. If assessment of non-motor features could be combined with an overview of motor fluctuations this could be very useful in management. The same wearable monitoring system described above for motor symptoms has also shown evidence for the assessment of daytime somnolence (3), and there is emerging evidence for detecting impulsive behaviours (4).
The development of these technological approaches to monitoring Parkinson’s has started to show clinical impact. Wearable technologies have begun to be used in routine clinical practice and are proving their worth in assessment of motor as well as non-motor symptoms. The use of wearable technologies in assessing suitability for non-oral therapies, as well as potentially assessing their efficacy, is an expanding area of use. A further challenge for these technologies is to make them more interactive, allowing people with Parkinson’s to adjust their therapy in response to direct feedback. Future clinical trials are likely to make use of automated measures of motor and non-motor features. Finally, the data from these devices will contribute to better knowledge of different subtypes of Parkinson’s and their optimal treatment, helping us progress to truly personalised medicine for Parkinson’s.
- Maetzler W, Klucken J, Horne M. A clinical view on the development of technology-based tools in managing Parkinson’s disease. Mov Disord. 2016;31(9):1263-71.
- Horne MK, McGregor S, Bergquist F. An objective fluctuation score for Parkinson’s disease. PloS one. 2015;10(4):e0124522.
- Kotschet K, Johnson W, McGregor S, Kettlewell J, Kyoong A, O’Driscoll DM, et al. Daytime sleep in Parkinson’s disease measured by episodes of immobility. Parkinsonism Relat Disord. 2014;20(6):578-83.
- Evans AH, Kettlewell J, McGregor S, Kotschet K, Griffiths RI, Horne M. A conditioned response as a measure of impulsive-compulsive behaviours in Parkinson’s disease. PloS one. 2014;9(2):e89319.
Dr Christopher Kobylecki, Consultant Neurologist, Greater Manchester Neurosciences Centre, Salford
Parkinson’s KinetiGraph™ (PKG™) is a movement-recording medical device that clinicians can use as part of their treatment and management programmes for patients with Parkinson’s Disease (PD). Its main component is the PKG™ Data Logger, a wrist-worn device similar to a large watch that automatically records patients’ movement pattern data. The recorded information is then analysed and graphically presented in a PKG™ report, where the median of a control group movement pattern is used as comparison.
By providing an objective and continuous quantification of the movement disorder symptoms bradykinesia and dyskinesia as experienced in the home environment during activities of daily living, the PKG™ Data Logger overcomes many of the limitations of traditional movement disorder assessments made via momentary clinical impressions or patient self-reporting, which often proves to be unreliable (2). As well as showing direct responses to treatment, the device also helps clinicians and neurologists better understand the nature and progression of the disease.
Download a case to learn more about how the PKG™ can optimise treatment regime and reveal unrecognised dose-related wearing off in PD patients.
- Robert I. Griffiths, Katya Kotschet, Sian Arfona, Zheng Ming Xud, William Johnson, John Dragoa, Andrew Evans, Peter Kempster,1. Sanjay Raghav and Malcolm K. Horne. Automated assessment of Bradykinesia and Dyskinesia in Parkinson´s Disease.Journal of Parkinson´s disease 2, 47 (2012)
- Filip Bergquist and Malcolm Horne. Can Objective Measurements Improve Treatment Outcomes in Parkinson´s Disease?3. European Neurological Review 1, 9, (2014)