How Time Rules: Diurnal Motor Patterns in de novo Parkinson’s Disease

An Exploration of Wearable Device Features Used in UK Hospital Parkinson Disease Care: Scoping Review

BACKGROUND

The prevalence of Parkinson disease (PD) is becoming an increasing concern owing to the aging population in the United Kingdom. Wearable devices have the potential to improve the clinical care of patients with PD while reducing health care costs. Consequently, exploring the features of these wearable devices is important to identify the limitations and further areas of investigation of how wearable devices are currently used in clinical care in the United Kingdom.

OBJECTIVE

In this scoping review, we aimed to explore the features of wearable devices used for PD in hospitals in the United Kingdom.

METHODS

A scoping review of the current research was undertaken and reported according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. The literature search was undertaken on June 6, 2022, and publications were obtained from MEDLINE or PubMed, Embase, and the Cochrane Library. Eligible publications were initially screened by their titles and abstracts. Publications that passed the initial screening underwent a full review. The study characteristics were extracted from the final publications, and the evidence was synthesized using a narrative approach. Any queries were reviewed by the first and second authors.

RESULTS

Of the 4543 publications identified, 39 (0.86%) publications underwent a full review, and 20 (0.44%) publications were included in the scoping review. Most studies (11/20, 55%) were conducted at the Newcastle upon Tyne Hospitals NHS Foundation Trust, with sample sizes ranging from 10 to 418. Most study participants were male individuals with a mean age ranging from 57.7 to 78.0 years. The AX3 was the most popular device brand used, and it was commercially manufactured by Axivity. Common wearable device types included body-worn sensors, inertial measurement units, and smartwatches that used accelerometers and gyroscopes to measure the clinical features of PD. Most wearable device primary measures involved the measured gait, bradykinesia, and dyskinesia. The most common wearable device placements were the lumbar region, head, and wrist. Furthermore, 65% (13/20) of the studies used artificial intelligence or machine learning to support PD data analysis.

CONCLUSIONS

This study demonstrated that wearable devices could help provide a more detailed analysis of PD symptoms during the assessment phase and personalize treatment. Using machine learning, wearable devices could differentiate PD from other neurodegenerative diseases. The identified evidence gaps include the lack of analysis of wearable device cybersecurity and data management. The lack of cost-effectiveness analysis and large-scale participation in studies resulted in uncertainty regarding the feasibility of the widespread use of wearable devices. The uncertainty around the identified research gaps was further exacerbated by the lack of medical regulation of wearable devices for PD, particularly in the United Kingdom where regulations were changing due to the political landscape.

Circadian profile, daytime activity, and the Parkinson's phenotype: A motion sensor pilot study with neurobiological underpinnings

Circadian rhythm impairment may play a role in Parkinson's disease (PD) pathophysiology. Recent literature associated circadian rhythm features to the risk of developing Parkinson and to its progression through stages. The association between the chronotype and the phenotype should be verified on a clinical and biological point of view. Herein we investigate the chronotype of a sample of 50 PD patients with the Morningness Eveningness Questionnaire and monitor their daily activity with a motion sensor embedded in a smartphone. Fibroblasts were collected from PD patients (n = 5) and from sex/age matched controls (n = 3) and tested for the circadian expression of clock genes (CLOCK, BMAL1, PER1, CRY1), and for cell morphology, proliferation, and death. Our results show an association between the chronotype and the PD phenotype. The most representative clinical chronotypes were "moderate morning" (56%), the "intermediate" (24%) and, in a minor part, the "definite morning" (16%). They differed for axial motor impairment, presence of motor fluctuations and quality of life (p < 0.05). Patients with visuospatial dysfunction and patients with a higher PIGD score had a blunted motor daily activity (p = 0.006 and p = 0.001, respectively), independently by the influence of age and other motor scores. Fibroblasts obtained by PD patients (n = 5) had an impaired BMAL1 cycle compared to controls (n = 3, p = 0.01). Moreover, a PD flat BMAL1 profile was associated with the lowest cell proliferation and the largest cell morphology. This study contributes to the growing literature on CR abnormalities in the pathophysiology of Parkinson's disease providing a link between the clinical and biological patient chronotype and the disease phenomenology.

The multimodal effect of circadian interventions in Parkinson's disease: A narrative review

BACKGROUND

The circadian system and its dysfunction in persons with Parkinson's disease (PwP) has a clear impact on both motor and non-motor symptoms. Examples include circadian patterns in motor disability, with worsening of symptoms throughout the day, but also the existence of similar patterns in non-motor symptoms.

OBJECTIVE

In this narrative review, we discuss the role of the circadian system, we address the role of dopamine in this system, and we summarise the evidence that supports the use of circadian system treatments for motor and non-motor symptoms in PwP.

METHODS

A systematic search in PubMed and Web of Science database was performed and the final search was performed in November 2021. We included articles whose primary aim was to investigate the effect of melatonin, melatonin agonists, and light therapy in PwP.

RESULTS

In total 25 articles were retrieved. Of these, 12 were related to bright light therapy and 13 to melatonin or/and melatonin agonists. Most, but not all, studies showed that melatonin and melatonin agonists and light therapy induced improvements in measures of sleep, depression, motor function, and some also cognitive function and other non-motor symptoms. For some of these outcomes, including daytime sleepiness, depressive symptoms, and some motor symptoms, there is level 2 B evidence for the use of circadian treatments in PwP.

CONCLUSIONS

Treatment with bright light therapy, exogenous melatonin and melatonin agonists seems to have not only positive effects on sleep quality and depression but also on motor function in PwP. Drawbacks in earlier work include the relatively small number of participants and the heterogeneity of outcome measures. Further large and well-designed trials are needed to address these shortcomings and to confirm or refute the possible merits of the circadian system as a treatment target in PwP.

Quality of life: Seasonal fluctuation in Parkinson's disease

Objective

Although the seasonal variation of motor and non-motor symptoms in Parkinson's disease (PD) has been reported, the association between seasonal change and quality of life in patients with Parkinson's disease remains to be explored.

Methods

We recruited 1,036 patients with PD in this cross-sectional retrospective study. The patients were divided into four groups based on their date of assessment, according to the classical four seasons: group 1: March to May (n = 241); group 2: June to August (n = 259); group 3: September to November(n = 273); group 4: December to February (n = 263). The 39-item Parkinson's Disease Questionnaire (PDQ-39) and other clinical evaluation scales for motor and non-motor symptoms were administered. The determinants of the quality of life (QoL) were analyzed by multiple stepwise regression analyses.

Results

A significant difference in PDQ-39 was found between group 1 (spring months) and group 3 (autumn months) after correction (p = 0.002). The Unified Parkinson's Disease Rating Scale part III (UPDRS-III) score was higher in group 1 (spring months) than in group 3 (the autumn months) (p = 0.033). The most severe determinant of QoL was the UPDRS-III score in group 1 and the Geriatric Depression Scale (GDS) score in groups 2, 3, and 4.

Interpretation

The current study reported seasonal fluctuation of QoL in patients with PD, with higher scores during the spring months and lower scores in the autumn months. Since the determinants for QoL also vary by season, clinicians might need to focus on specific factors across seasons before initiating therapy.

The role of wrist-worn technology in the management of Parkinson's disease in daily life: A narrative review

Parkinson's disease (PD) is a neurodegenerative disorder that affects millions of people worldwide. Its slow and heterogeneous progression over time makes timely diagnosis challenging. Wrist-worn digital devices, particularly smartwatches, are currently the most popular tools in the PD research field due to their convenience for long-term daily life monitoring. While wrist-worn sensing devices have garnered significant interest, their value for daily practice is still unclear. In this narrative review, we survey demographic, clinical and technological information from 39 articles across four public databases. Wrist-worn technology mainly monitors motor symptoms and sleep disorders of patients in daily life. We find that accelerometers are the most commonly used sensors to measure the movement of people living with PD. There are few studies on monitoring the disease progression compared to symptom classification. We conclude that wrist-worn sensing technology might be useful to assist in the management of PD through an automatic assessment based on patient-provided daily living information.

Why do 'OFF' periods still occur during continuous drug delivery in Parkinson's disease?

Continuous drug delivery (CDD) is used in moderately advanced and late-stage Parkinson’s disease (PD) to control motor and non-motor fluctuations (‘OFF’ periods). Transdermal rotigotine is indicated for early fluctuations, while subcutaneous apomorphine infusion and levodopa-carbidopa intestinal gel are utilised in advanced PD. All three strategies are considered examples of continuous dopaminergic stimulation achieved through CDD. A central premise of the CDD is to achieve stable control of the parkinsonian motor and non-motor states and avoid emergence of ‘OFF’ periods. However, data suggest that despite their efficacy in reducing the number and duration of ‘OFF’ periods, these strategies still do not prevent ‘OFF’ periods in the middle to late stages of PD, thus contradicting the widely held concepts of continuous drug delivery and continuous dopaminergic stimulation. Why these emergent ‘OFF’ periods still occur is unknown. In this review, we analyse the potential reasons for their persistence. The contribution of drug- and device-related involvement, and the problems related to site-specific drug delivery are analysed. We propose that changes in dopaminergic and non-dopaminergic mechanisms in the basal ganglia might render these persistent ‘OFF’ periods unresponsive to dopaminergic therapy delivered via CDD.

An Exploration of Wearable Device Features Used in UK Hospital Parkinson Disease Care: Scoping Review (Preprint).. [DOI: 10.2196/preprints.42950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

BACKGROUND

The prevalence of Parkinson disease (PD) is becoming an increasing concern owing to the aging population in the United Kingdom. Wearable devices have the potential to improve the clinical care of patients with PD while reducing health care costs. Consequently, exploring the features of these wearable devices is important to identify the limitations and further areas of investigation of how wearable devices are currently used in clinical care in the United Kingdom.

OBJECTIVE

In this scoping review, we aimed to explore the features of wearable devices used for PD in hospitals in the United Kingdom.

METHODS

A scoping review of the current research was undertaken and reported according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. The literature search was undertaken on June 6, 2022, and publications were obtained from MEDLINE or PubMed, Embase, and the Cochrane Library. Eligible publications were initially screened by their titles and abstracts. Publications that passed the initial screening underwent a full review. The study characteristics were extracted from the final publications, and the evidence was synthesized using a narrative approach. Any queries were reviewed by the first and second authors.

RESULTS

Of the 4543 publications identified, 39 (0.86%) publications underwent a full review, and 20 (0.44%) publications were included in the scoping review. Most studies (11/20, 55%) were conducted at the Newcastle upon Tyne Hospitals NHS Foundation Trust, with sample sizes ranging from 10 to 418. Most study participants were male individuals with a mean age ranging from 57.7 to 78.0 years. The AX3 was the most popular device brand used, and it was commercially manufactured by Axivity. Common wearable device types included body-worn sensors, inertial measurement units, and smartwatches that used accelerometers and gyroscopes to measure the clinical features of PD. Most wearable device primary measures involved the measured gait, bradykinesia, and dyskinesia. The most common wearable device placements were the lumbar region, head, and wrist. Furthermore, 65% (13/20) of the studies used artificial intelligence or machine learning to support PD data analysis.

CONCLUSIONS

This study demonstrated that wearable devices could help provide a more detailed analysis of PD symptoms during the assessment phase and personalize treatment. Using machine learning, wearable devices could differentiate PD from other neurodegenerative diseases. The identified evidence gaps include the lack of analysis of wearable device cybersecurity and data management. The lack of cost-effectiveness analysis and large-scale participation in studies resulted in uncertainty regarding the feasibility of the widespread use of wearable devices. The uncertainty around the identified research gaps was further exacerbated by the lack of medical regulation of wearable devices for PD, particularly in the United Kingdom where regulations were changing due to the political landscape.

CLINICALTRIAL

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Characterisation of non‐motor fluctuations using the Movement Disorder Society Non‐Motor Rating Scale

Background

Non‐motor fluctuations (NMF) in people with Parkinson's disease (PwP) are clinically important yet understudied.

Objective

To study NMF in PwP using both the Movement Disorder Society Non‐Motor Rating Scale (MDS‐NMS) NMF subscale and wearable sensors.

Methods

We evaluated differences in overall burden of NMF and of specific NMF across disease durations: <2 years (n = 33), 2–5 years (n = 35), 5–10 years (n = 33), and > 10 years (n = 31). In addition, wearable triaxial sensor output was used as an exploratory outcome for early morning “off” periods.

Results

Significant between‐group differences were observed for MDS‐NMS NMF total scores (P < 0.001), and specifically for depression, anxiety, fatigue and cognition, with both NMF prevalence and burden increasing in those with longer disease duration. Whereas only 9.1% with a short disease duration had NMF (none of whom had dyskinesia), in PwP with a disease duration of >10 years this was 71.0% (P < 0.001). From a motor perspective, dyskinesia severity increased evenly with increasing disease duration, while NMF scores in affected individuals showed an initial increase with largest differences between 2–5 years disease duration (P < 0.001), with plateauing afterwards. Finally, we observed that the most common NMF symptoms in patients with sensor‐confirmed early morning “off” periods were fluctuations in cognitive capabilities, restlessness, and excessive sweating.

Conclusions

Non‐motor fluctuations prevalence in PwP increases with disease duration, but in a pattern different from motor fluctuations. Moreover, NMF can occur in PwP without dyskinesia, and in those with NMF the severity of NMF increases most during years 2–5 after diagnosis.

Association of serum cholesterol with Parkinson's disease in a cohort of statin-free individuals

INTRODUCTION

The role of serum cholesterol in the pathogenesis of Parkinson's disease (PD) remains unclear. The objective of this study was to assess the association between serum cholesterol and PD in a cohort of statin-free newly diagnosed PD patients.

METHODS

This retrospective study used fasting lipid profiles obtained from 672 consecutive statin-free newly diagnosed PD individuals and 540 controls. These PD individuals were identified from three medical institutions during 2017-2021, and the controls were identified from three physical examination centers during the same time period. Logistic regressions were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs), with adjustment of age, sex, and tobacco use history.

RESULTS

Among 672 PD individuals, 112 were excluded in accordance with the current criteria, leaving 560 PD patients. The multivariate binary logistic regression analysis showed that LDL-C was the only variable contributing to the occurrence of PD (OR 1.39, 95% CI: 1.07-2.31, p < .001) after adjusting for age, sex, and tobacco use history; this association persisted following further adjustment for TC and HDL-C. In the subgroup analysis of the adjusted results of LDL-C after correcting for TC and HDL-C, lower LDL-C was associated with a higher risk of PD.

CONCLUSION

Among selected populations of statin-free newly diagnosed PD individuals, low LDL-C might be associated with the occurrence of PD.

Digital health technology for non-motor symptoms in people with Parkinson's disease: Futile or future?

INTRODUCTION

There is an ongoing digital revolution in the field of Parkinson's disease (PD) for the objective measurement of motor aspects, to be used in clinical trials and possibly support therapeutic choices. The focus of remote technologies is now also slowly shifting towards the broad but more "hidden" spectrum of non-motor symptoms (NMS).

METHODS

A narrative review of digital health technologies for measuring NMS in people with PD was conducted. These digital technologies were defined as assessment tools for NMS offered remotely in the form of a wearable, downloadable as a mobile app, or any other objective measurement of NMS in PD that did not require a hospital visit and could be performed remotely. Searches were performed using peer-reviewed literature indexed databases (MEDLINE, Embase, PsycINFO, Cochrane Database of Systematic Reviews, Cochrane CENTRAL Register of Controlled Trials), as well as Google and Google Scholar.

RESULTS

Eighteen studies deploying digital health technology in PD were identified, for example for the measurement of sleep disorders, cognitive dysfunction and orthostatic hypotension. In addition, we describe promising developments in other conditions that could be translated for use in PD.

CONCLUSION

Unlike motor symptoms, non-motor features of PD are difficult to measure directly using remote digital technologies. Nonetheless, it is currently possible to reliably measure several NMS and further digital technology developments are underway to offer further capture of often under-reported and under-recognised NMS.