Novel methods of symptom measurement in Parkinson's disease

Abstract

Parkinsons Disease is a common neurodegenerative disorder characterized by bradykinesia, rigidity, gait impairment and rest tremor. Non-motor features including anosmia, Rapid eye movement sleep behavior disorder, autonomic dysfunction, neuropsychiatric manifestations and cognitive changes are increasing recognized. The course of Parkinsons Disease is a progressive one and symptoms can fluctuate hour to hour. As such, symptom measurement plays a vital role by generating quantifiable targets to facilitate monitoring of disease progression and treatment response. In the absence of a reliable biomarker, symptom measurement is the cornerstone upon which diagnosis and clinical decisions are made and prognosis is gauged.

Conventional methods of subjective symptom reporting and validated objective clinical rating scales, to more contemporary approaches of technology-based quantitative measurement methods all have their unique strengths and shortcomings. While motor symptoms have more measurable physical properties, the best targets and the optimal method and platform to use remain unclear. Measurement of non-motor symptoms proves to be more challenging and remains a glaring gap in this field. A more measurable non-motor problem is cognitive impairment, which can be present even in the early stages of Parkinsons Disease. Cognitive assessment has both diagnostic and prognostic implications. However, it is uncertain which tests are most useful and more modern computerized approaches have not been extensively or rigorously studied. This compilation focuses on novel approaches and methods of measurement of motor and cognitive symptoms in Parkinsons Disease. Short and simple screening tests were developed. Specifically, motor symptoms were assessed and measured using smartphone technology and a self-reporting questionnaire. Following a critical statistical appraisal of the literature on cognitive assessment in parkinsonian disorders, a smartphone based cognitive test was developed to assess executive dysfunction.

The aims of this compilation are:

To establish the feasibility of using smartphone technology to measure motor deficits and cognition in patients with Parkinsons Disease by validation of a purpose built application;

To examine the pros and cons of objective motor assessment versus subjective symptom reporting by comparing the validated smartphone application and a self-reporting questionnaire using the clinical example of a motor phenomenon known as sleep benefit and

To interpret existing literature on the role of cognitive assessment in the diagnosis of Parkinsons Disease and other parkinsonian disorders using an innovative statistical approach.