Tossing and Turning in Bed: Nocturnal Movements in Parkinson's Disease

Digital biomarkers for non-motor symptoms in Parkinson's disease: the state of the art

Digital biomarkers that remotely monitor symptoms have the potential to revolutionize outcome assessments in future disease-modifying trials in Parkinson's disease (PD), by allowing objective and recurrent measurement of symptoms and signs collected in the participant's own living environment. This biomarker field is developing rapidly for assessing the motor features of PD, but the non-motor domain lags behind. Here, we systematically review and assess digital biomarkers under development for measuring non-motor symptoms of PD. We also consider relevant developments outside the PD field. We focus on technological readiness level and evaluate whether the identified digital non-motor biomarkers have potential for measuring disease progression, covering the spectrum from prodromal to advanced disease stages. Furthermore, we provide perspectives for future deployment of these biomarkers in trials. We found that various wearables show high promise for measuring autonomic function, constipation and sleep characteristics, including REM sleep behavior disorder. Biomarkers for neuropsychiatric symptoms are less well-developed, but show increasing accuracy in non-PD populations. Most biomarkers have not been validated for specific use in PD, and their sensitivity to capture disease progression remains untested for prodromal PD where the need for digital progression biomarkers is greatest. External validation in real-world environments and large longitudinal cohorts remains necessary for integrating non-motor biomarkers into research, and ultimately also into daily clinical practice.

Devices for remote continuous monitoring of people with Parkinson's disease: a systematic review and cost-effectiveness analysis

Background

Parkinson's disease is a brain condition causing a progressive loss of co ordination and movement problems. Around 145,500 people have Parkinson's disease in the United Kingdom. Levodopa is the most prescribed treatment for managing motor symptoms in the early stages. Patients should be monitored by a specialist every 6-12 months for disease progression and treatment of adverse effects. Wearable devices may provide a novel approach to management by directly monitoring patients for bradykinesia, dyskinesia, tremor and other symptoms. They are intended to be used alongside clinical judgement.

Objectives

To determine the clinical and cost-effectiveness of five devices for monitoring Parkinson's disease: Personal KinetiGraph, Kinesia 360, KinesiaU, PDMonitor and STAT-ON.

Methods

We performed systematic reviews of all evidence on the five devices, outcomes included: diagnostic accuracy, impact on decision-making, clinical outcomes, patient and clinician opinions and economic outcomes. We searched MEDLINE and 12 other databases/trial registries to February 2022. Risk of bias was assessed. Narrative synthesis was used to summarise all identified evidence, as the evidence was insufficient for meta-analysis. One included trial provided individual-level data, which was re-analysed. A de novo decision-analytic model was developed to estimate the cost-effectiveness of Personal KinetiGraph and Kinesia 360 compared to standard of care in the UK NHS over a 5-year time horizon. The base-case analysis considered two alternative monitoring strategies: one-time use and routine use of the device.

Results

Fifty-seven studies of Personal KinetiGraph, 15 of STAT-ON, 3 of Kinesia 360, 1 of KinesiaU and 1 of PDMonitor were included. There was some evidence to suggest that Personal KinetiGraph can accurately measure bradykinesia and dyskinesia, leading to treatment modification in some patients, and a possible improvement in clinical outcomes when measured using the Unified Parkinson's Disease Rating Scale. The evidence for STAT-ON suggested it may be of value for diagnosing symptoms, but there is currently no evidence on its clinical impact. The evidence for Kinesia 360, KinesiaU and PDMonitor is insufficient to draw any conclusions on their value in clinical practice. The base-case results for Personal KinetiGraph compared to standard of care for one-time and routine use resulted in incremental cost-effectiveness ratios of £67,856 and £57,877 per quality-adjusted life-year gained, respectively, with a beneficial impact of the Personal KinetiGraph on Unified Parkinson's Disease Rating Scale domains III and IV. The incremental cost-effectiveness ratio results for Kinesia 360 compared to standard of care for one-time and routine use were £38,828 and £67,203 per quality-adjusted life-year gained, respectively.

Limitations

The evidence was limited in extent and often low quality. For all devices, except Personal KinetiGraph, there was little to no evidence on the clinical impact of the technology.

Conclusions

Personal KinetiGraph could reasonably be used in practice to monitor patient symptoms and modify treatment where required. There is too little evidence on STAT-ON, Kinesia 360, KinesiaU or PDMonitor to be confident that they are clinically useful. The cost-effectiveness of remote monitoring appears to be largely unfavourable with incremental cost-effectiveness ratios in excess of £30,000 per quality-adjusted life-year across a range of alternative assumptions. The main driver of cost-effectiveness was the durability of improvements in patient symptoms.

Study registration

This study is registered as PROSPERO CRD42022308597.

Funding

This award was funded by the National Institute for Health and Care Research (NIHR) Evidence Synthesis programme (NIHR award ref: NIHR135437) and is published in full in Health Technology Assessment; Vol. 28, No. 30. See the NIHR Funding and Awards website for further award information.

Old problems, new solutions: harnessing technology and innovation in Parkinson's disease-evidence and experiences from Thailand

The prevalence of Parkinson's disease (PD) is increasing rapidly worldwide, but there are notable inequalities in its distribution and in the availability of healthcare resources across different world regions. Low- and middle-income countries (LMICs), including Thailand, bear the highest burden of PD so there is an urgent need to develop effective solutions that can overcome the many regional challenges associated with delivering high-quality, and equitable care to a diverse population with limited resources. This article describes the evolution of healthcare delivery for PD in Thailand, as a case example of a LMIC. The discussions reflect the author's presentation at the Yoshikuni Mizuno Lectureship Award given during the 8th Asian and Oceanian Parkinson's Disease and Movement Disorders Congress in March 2023 for which he was the 2023 recipient. The specific challenges faced in Thailand are reviewed along with new solutions that have been implemented to improve the knowledge and skills of healthcare professionals nationally, the delivery of care, and the outcomes for PD patients. Technology and innovation have played an important role in this process with many new tools and devices being implemented in clinical practice. Without any realistic prospect of a curative therapy in the near future that could halt the current PD pandemic, it will be necessary to focus on preventative lifestyle strategies that can help reduce the risk of developing PD such as good nutrition (EAT), exercise (MOVE), good sleep hygiene (SLEEP), and minimizing environmental risks (PROTECT), which should be initiated and continued (REPEAT) as early as possible.

Too little or too much nocturnal movements in Parkinson's disease: A practical guide to managing the unseen

Nocturnal and sleep-related motor disorders in people with Parkinson's disease (PD) have a wide spectrum of manifestations and present a complex clinical picture. Problems can arise due to impaired movement ability (hypokinesias), e.g. nocturnal hypokinesia or early-morning akinesia, or to excessive movement (hyperkinesias), e.g. end-of-the-day dyskinesia, parasomnias, periodic limb movement during sleep and restless legs syndrome. These disorders can have a significant negative impact on the sleep, daytime functional ability, and overall quality of life of individuals with PD and their carers. The debilitating motor issues are often accompanied by a combination of non-motor symptoms, including pain and cramping, which add to the overall burden. Importantly, nocturnal motor disorders encompass a broader timeline than just the period of sleep, often starting in the evening, as well as occurring throughout the night and on awakening, and are not just limited to problems of insomnia or sleep fragmentation. Diagnosis can be challenging as, in many cases, the 'gold standard' assessment method is video polysomnography, which may not be available in all settings. Various validated questionnaires are available to support evaluation, and alternative approaches, using wearable sensors and digital technology, are now being developed to facilitate early diagnosis and monitoring. This review sets out the parameters of what can be considered normal nocturnal movement and describes the clinical manifestations, usual clinical or objective assessment methods, and evidence for optimal management strategies for the common nocturnal motor disorders that neurologists will encounter in people with PD in their clinical practice.

Digital Mobility Measures: A Window into Real-World Severity and Progression of Parkinson's Disease

BACKGROUND

Real-world monitoring using wearable sensors has enormous potential for assessing disease severity and symptoms among persons with Parkinson's disease (PD). Many distinct features can be extracted, reflecting multiple mobility domains. However, it is unclear which digital measures are related to PD severity and are sensitive to disease progression.

OBJECTIVES

The aim was to identify real-world mobility measures that reflect PD severity and show discriminant ability and sensitivity to disease progression, compared to the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) scale.

METHODS

Multicenter real-world continuous (24/7) digital mobility data from 587 persons with PD and 68 matched healthy controls were collected using an accelerometer adhered to the lower back. Machine learning feature selection and regression algorithms evaluated associations of the digital measures using the MDS-UPDRS (I-III). Binary logistic regression assessed discriminatory value using controls, and longitudinal observational data from a subgroup (n = 33) evaluated sensitivity to change over time.

RESULTS

Digital measures were only moderately correlated with the MDS-UPDRS (part II-r = 0.60 and parts I and III-r = 0.50). Most associated measures reflected activity quantity and distribution patterns. A model with 14 digital measures accurately distinguished recently diagnosed persons with PD from healthy controls (81.1%, area under the curve: 0.87); digital measures showed larger effect sizes (Cohen's d: [0.19-0.66]), for change over time than any of the MDS-UPDRS parts (Cohen's d: [0.04-0.12]).

CONCLUSIONS

Real-world mobility measures are moderately associated with clinical assessments, suggesting that they capture different aspects of motor capacity and function. Digital mobility measures are sensitive to early-stage disease and to disease progression, to a larger degree than conventional clinical assessments, demonstrating their utility, primarily for clinical trials but ultimately also for clinical care. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

The Importance of Digital Health Literacy in an Evolving Parkinson's Disease Care System

Digital health technologies are growing at a rapid pace and changing the healthcare landscape. Our current understanding of digital health literacy in Parkinson's disease (PD) is limited. In this review, we discuss the potential challenges of low digital health literacy in PD with particular attention to telehealth, deep brain stimulation, wearable sensors, and smartphone applications. We also highlight inequities in access to digital health technologies. Future research is needed to better understand digital health literacy among individuals with PD and to develop effective solutions. We must invest resources to evaluate, understand, and enhance digital health literacy for individuals with PD.

Exploring the Association Linking Head Position and Sleep Architecture to Motor Impairment in Parkinson's Disease: An Exploratory Study

Patients with Parkinson's disease (PD) tend to sleep more frequently in the supine position and less often change head and body position during sleep. Besides sleep quality and continuity, head and body positions are crucial for glymphatic system (GS) activity. This pilot study evaluated sleep architecture and head position during each sleep stage in idiopathic PD patients without cognitive impairment, correlating sleep data to patients' motor and non-motor symptoms (NMS). All patients underwent the multi-night recordings, which were acquired using the Sleep Profiler headband. Sleep parameters, sleep time in each head position, and percentage of slow wave activity (SWA) in sleep, stage 3 of non-REM sleep (N3), and REM sleep in the supine position were extracted. Lastly, correlations with motor impairment and NMS were performed. Twenty PD patients (65.7 ± 8.6 y.o, ten women) were included. Sleep architecture did not change across the different nights of recording and showed the prevalence of sleep performed in the supine position. In addition, SWA and N3 were more frequently in the supine head position, and N3 in the supine decubitus correlated with REM sleep performed in the same position; this latter correlated with the disease duration (correlation coefficient = 0.48, p-value = 0.03) and motor impairment (correlation coefficient = 0.53, p-value = 0.02). These preliminary results demonstrated the importance of monitoring sleep in PD patients, supporting the need for preventive strategies in clinical practice for maintaining the lateral head position during the crucial sleep stages (SWA, N3, REM), essential for permitting the GS function and activity and ensuring brain health.

Assessing impaired bed mobility in patients with Parkinson's disease: a scoping review

BACKGROUND

Although most patients with Parkinson's disease (PD) experience difficulties in bed mobility, evidence on the suitability of the methods for assessing impaired bed mobility in PD are lacking.

OBJECTIVES

To identify objective methods for assessing impaired bed mobility in PD and to discuss their clinimetric properties and feasibility for use in clinical practice.

DATA SOURCES

PubMed, Web of Science, and Cochrane Library were searched between 1995 and 2022.

SELECTION CRITERIA

Studies were included if they described an objective assessment method for assessing impaired bed mobility in PD.

DATA EXTRACTION AND DATA SYNTHESIS

Characteristics of the identified measurement methods such as clinimetric properties and feasibility were extracted by two authors. The methodological quality of studies was evaluated using the Appraisal of studies tool.

RESULTS

Twenty-three studies were included and categorised into three assessment methods: sensor-based assessments (48%), rating scales (39%), and timed-tests (13%). The risk of bias was low for all but one study, which was medium.

LIMITATIONS

Despite applying wide selection criteria, a relatively small number of studies were identified in our results.

CONCLUSION

Rating scales may be the most preferred for assessing impaired bed mobility in PD in clinical practice, until clinimetric validity are adequately demonstrated in the other assessment methods. CONTRIBUTION OF PAPER.

Monitoring sleep stages with a soft electrode array: Comparison against vPSG and home-based detection of REM sleep without atonia

Sleep disorders are symptomatic hallmarks of a variety of medical conditions. Accurately identifying the specific stage in which these disorders occur is particularly important for the correct diagnosis of non-rapid eye movement and rapid eye movement parasomnias. In-lab polysomnography suffers from limited availability and does not reflect habitual sleep conditions, which is especially important in older adults and those with neurodegenerative diseases. We aimed to explore the feasibility and validity of a new wearable system for accurately measuring sleep at home. The system core technology is soft, printed dry electrode arrays and a miniature data acquisition unit with a cloud-based data storage for offline analysis. The positions of the electrodes allow manual scoring following the American Association of Sleep Medicine guidelines. Fifty participants (21 healthy subjects, mean age 56.6 ± 8.4 years; and 29 patients with Parkinson's disease, 65.4 ± 7.6 years) underwent a polysomnography evaluation with parallel recording with the wearable system. Total agreement between the two systems reached Cohen's kappa (k) of 0.688 with agreement in each stage of: wake k = 0.701; N1 = 0.224; N2 = 0.584; N3 = 0.410; and rapid eye movement = 0.723. Moreover, the system reliably detected rapid eye movement sleep without atonia with a sensitivity of 85.7%. Additionally, a comparison between sleep as measured in the sleep lab with data collected from a night at home showed significantly lower wake after sleep onset at home. The results demonstrate that the system is valid, accurate and allows for the exploration of sleep at home. This new system offers an opportunity to help detect sleep disorders on a larger scale than possible today, fostering better care.

Objective measurement versus clinician-based assessment for Parkinson's disease

INTRODUCTION

Although clinician-based assessment through standardized clinical rating scales is currently the gold standard for quantifying motor impairment in Parkinson's disease (PD), it is not without limitations, including intra- and inter-rater variability and a degree of approximation. There is increasing evidence supporting the use of objective motion analyses to complement clinician-based assessment. Objective measurement tools hold significant potential for improving the accuracy of clinical and research-based evaluations of patients.

AREAS COVERED

The authors provide several examples from the literature demonstrating how different motion measurement tools, including optoelectronics, contactless and wearable systems allow for both the objective quantification and monitoring of key motor symptoms (such as bradykinesia, rigidity, tremor, and gait disturbances), and the identification of motor fluctuations in PD patients. Furthermore, they discuss how, from a clinician's perspective, objective measurements can help in various stages of PD management.

EXPERT OPINION

In our opinion, sufficient evidence supports the assertion that objective monitoring systems enable accurate evaluation of motor symptoms and complications in PD. A range of devices can be utilized not only to support diagnosis but also to monitor motor symptom during the disease progression and can become relevant in the therapeutic decision-making process.

Measurement instruments to assess basic functional mobility in Parkinson's Disease: A systematic review of clinimetric properties and feasibility for use in clinical practice

Taniguchi S, Yamamoto A. Measurement instruments to assess basic functional mobility in Parkinson's Disease: A systematic review of clinimetric properties and feasibility for use in clinical practice. Jpn J Compr Rehabil Sci 2023; 14: 16-25.

Objective

To systematically review the evaluation of clinimetric properties and feasibility of the "Modified Parkinson Activity Scale (M-PAS)" and the "Lindop Parkinson's Disease Mobility Assessment (LPA)," which are Parkinson's Disease (PD)-specific measurement instruments to assess basic functional mobility, and to discuss their considerations for use in clinical practice.

Methods

A systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A risk of bias assessment was also performed.

Results

Eleven studies were included: five studies used M-PAS (45%), five studies used LPA (45%), and one study used M-PAS and LPA (13%). The risk of bias was low for all evaluated studies.

Conclusion

M-PAS and LPA showed adequate reliability, validity, and responsiveness in detecting intervention changes. M-PAS has more detailed qualitative scoring options, a lack of ceiling effect, and can be used by a non-expert in PD.In contrast, the drawback of M-PAS is that it is time-consuming to apply in everyday clinical practice. On the other hand, LPA with greater simplicity may lead to lower burdens for both patients and raters in situations with strict time limitations. Further research is required to identify new resources.

Role of novel endpoints and evaluations of response in Parkinson disease

With progress in our understanding of Parkinson disease (PD) and other neurodegenerative disorders, from clinical features to imaging, genetic, and molecular characterization comes the opportunity to refine and revise how we measure these diseases and what outcome measures are used as endpoints in clinical trials. While several rater-, patient-, and milestone-based outcomes for PD exist that may serve as clinical trial endpoints, there remains an unmet need for endpoints that are clinically meaningful, patient centric while also being more objective and quantitative, less susceptible to effects of symptomatic therapy (for disease-modification trials), and that can be measured over a short period and yet accurately represent longer-term outcomes. Several novel outcomes that may be used as endpoints in PD clinical trials are in development, including digital measures of signs and symptoms, as well a growing array of imaging and biospecimen biomarkers. This chapter provides an overview of the state of PD outcome measures as of 2022, including considerations for selection of clinical trial endpoints in PD, advantages and limitations of existing measures, and emerging potential novel endpoints.

Can Wearable Inertial Measurement Units Be Used to Measure Sleep Biomechanics? Establishing Initial Feasibility and Validity

Wearable motion sensors, specifically, Inertial Measurement Units, are useful tools for the assessment of orientation and movement during sleep. The DOTs platform (Xsens, Enschede, The Netherlands) has shown promise for this purpose. This pilot study aimed to assess its feasibility and validity for recording sleep biomechanics. Feasibility was assessed using four metrics: Drift, Battery Life, Reliability of Recording, and Participant Comfort. Each metric was rated as Stop (least successful), Continue But Modify Protocol, Continue But Monitor Closely, or Continue Without Modifications (most successful). A convenience sample of ten adults slept for one night with a DOT unit attached to their sternum, abdomen, and left and right legs. A survey was administered the following day to assess participant comfort wearing the DOTs. A subset of five participants underwent a single evaluation in a Vicon (Oxford Metrics, Oxford, UK) motion analysis lab to assess XSENS DOTs’ validity. With the two systems recording simultaneously, participants were prompted through a series of movements intended to mimic typical sleep biomechanics (rolling over in lying), and the outputs of both systems were compared to assess the level of agreement. The DOT platform performed well on all metrics, with Drift, Battery Life, and Recording Reliability being rated as Continue Without Modifications. Participant Comfort was rated as Continue But Monitor Closely. The DOT Platform demonstrated an extremely high level of agreement with the Vicon motion analysis lab (difference of <0.025°). Using the Xsens DOT platform to assess sleep biomechanics is feasible and valid in adult populations. Future studies should further investigate the feasibility of using this data capture method for extended periods (e.g., multiple days) and in other groups (e.g., paediatric populations).

Technological evaluation of strategies to get out of bed by people with Parkinson's disease: Insights from multisite wearable sensors

Background

Difficulty getting out of bed is a common night-time and early morning manifestation of Parkinson's disease (PD), rated by 40% of the patients as their most concerning motor symptoms. However, current assessment methods are based on clinical interviews, video analysis, and clinical scales as objective outcome measures are not yet available.

Objective

To study the technical feasibility of multisite wearable sensors in the assessment of the supine-to-stand (STS) task as a determinant of the ability to get out of bed in patients with PD and age-matched control subjects, and develop relevant objective outcome measures.

Methods

The STS task was assessed in 32 patients with PD (mean Hoehn and Yahr; HY = 2.5) in the early morning before their first dopaminergic medication, and in 14 control subjects, using multisite wearable sensors (NIGHT-Recorder®; trunk, both wrists, and both ankles) in a sleep laboratory. Objective getting out of bed parameters included duration, onset, velocity and acceleration of truncal rotation, and angle deviation (a°) from the z-axis when subjects rose from the bed at different angles from the x-axis (10°, 15°, 30°, 45°, and 60°) as measures of truncal lateral flexion. Movement patterns were identified from the first body part or parts that moved. Correlation analysis was performed between these objective outcomes and standard clinical rating scales.

Results

Compared to control subjects, the duration of STS was significantly longer in patients with PD (p = 0.012), which is associated with a significantly slower velocity of truncal rotation (p = 0.003). Moderate and significant correlations were observed between the mean STS duration and age, and the Nocturnal Hypokinesia Questionnaire. The velocity of truncal rotation negatively and significantly correlated with HY staging. Any arm and leg moved together as the first movement significantly correlated with UPDRS-Axial and item #28. Several other correlations were also observed.

Conclusion

Our study was able to demonstrate the technical feasibility of using multisite wearable sensors to quantitatively assess early objective outcome measures of the ability of patients with PD to get out of bed, which significantly correlated with axial severity scores, suggesting that axial impairment could be a contributing factor in difficulty getting out of bed. Future studies are needed to refine these outcome measures for use in therapeutic trials related to nocturia or early morning akinesia in PD.

Outcome Assessment in Parkinson Disease Prevention Trials: Utility of Clinical and Digital Measures

BACKGROUND AND OBJECTIVES

The prodromal phase of Parkinson disease (PD) is accompanied by subtle clinical signs that are not sufficient for diagnosis but could potentially be measured in the context of clinical trials of therapies intended to delay or prevent more definitive clinical features. The objective of this study was to review the available literature on the presence and time course of subtle motor features in prodromal PD in the context of planning for possible clinical trials.

METHODS

We reviewed the available literature based on expert opinion. We considered a range of outcomes including measurement of clinical features, patient-reported outcomes, digital markers, and clinical diagnosis.

RESULTS

We considered these features and measures in the context of patient stratification, intermediate outcomes, and clinically relevant end points, including phenoconversion.

DISCUSSION

Substantial progress has been made in understanding how motor features evolve in the period immediately before a PD diagnosis. Digital measures hold substantial progress for measurement precision and may be additionally relevant because they can be used in naturalistic environments outside the clinic. Future studies should focus on advancing digital sensor technology and analysis and developing methods to implement available methods, particularly determination of a clinical diagnosis of PD, in a clinical trial context.

Determinants of impaired bed mobility in Parkinson’s disease: Impact of hip muscle strength and motor symptoms

BACKGROUND: Although most patients with Parkinson’s disease (PD) present difficulties of bed mobility, the contributing factors to impaired bed mobility in PD are unknown. OBJECTIVE: To compare bed mobility and muscle strength between PD patients and healthy controls, and investigate the determinants of bed mobility in PD. METHODS: Sixteen patients with PD and ten age- and sex-matched healthy controls (HC) were enrolled. Time and pattern to get out of bed to their preferred side at usual speed, muscle torque in lower extremities and motor symptom burden were also measured. RESULTS: PD exhibited significantly slower speed in bed mobility and lower torque in the hip adductor/abductor/flexor muscle than HC. Slower movement time in PD was correlated with weaker hip adductor torque on the more affected side (Rs = –0.56, p < 0.05) and with higher score in arm rigidity both sides (Rs≥0.79, p < 0.01). There were no significant differences between the categorised movement patterns and movement time in PD (p = 0.31). CONCLUSIONS: Reduced hip adductors torque and severe arm rigidity are associated with slowness of getting out of bed, implying that these components could be used as targets for rehabilitation practice to improve bed mobility in PD.

Impaired bed mobility in prediagnostic and de novo Parkinson's disease

BACKGROUND

Wearable technology research suggests that nocturnal movements are disturbed in early Parkinson's disease (PD). In this study, we investigate if patients also already experience impaired bed mobility before PD diagnosis. Furthermore, we explore its association with motor and nonmotor features and its value for phenoconversion and disease progression prediction.

METHODS

PPMI data were downloaded for de novo PD subjects, subjects at-risk for developing a synucleinopathy (with isolated REM sleep behavior disorder, hyposmia or a pathogenic genetic variant) and controls. Impaired bed mobility was assessed with the MDS-UPDRS part 2 item 9. A frequency analysis was performed. Multivariable logistic regression analyses were used to investigate the association with other PD variables. Cox proportional-hazards models were used to test if difficulties with turning in bed could predict phenoconversion. Linear mixed models were used to evaluate if difficulties with turning in bed could predict disease progression.

RESULTS

Of the at-risk subjects, 9.2-12.5% experienced difficulties with turning in bed vs. 25.0% of de novo PD subjects and 2.5% of controls. Impaired turning ability was associated with MDS-UPDRS motorscore (axial signs in the at-risk group, bradykinesia in the de novo PD group) and SCOPA-AUT score (gastrointestinal symptoms). In addition, difficulties with turning in bed were a significant predictor for phenoconversion in the at-risk group and for development of motor complications in the de novo PD group.

CONCLUSION

Our findings suggest that difficulties with turning in bed can be helpful as clinical symptom for a prodromal PD screening and for motor complication prediction in early PD.

Moving Forward from the COVID-19 Pandemic: Needed Changes in Movement Disorders Care and Research

Purpose of Review

The COVID-19 pandemic has dramatically affected the health and well-being of individuals with movement disorders. This manuscript reviews these effects, discusses pandemic-related changes in clinical care and research, and suggests improvements to care and research models.

Recent Findings

During the on-going COVID-19 pandemic, individuals with movement disorders have experienced worsening of symptoms, likely due to decreased access to care, loss of social connection, and decreased physical activity. Through telemedicine, care has moved out of the clinic and into the home. Clinical research has also been significantly disrupted, and there has been a shift to decentralized approaches. The pandemic has highlighted disparities in access to care and representation in research.

Summary

We must now translate these experiences into better care and research models with a focus on equitable integration of telemedicine, better support of patients and caregivers, the development of meaningful digital endpoints, and optimization of decentralized research designs.

The Home-Based Sleep Laboratory

Sleep disturbances are prevalent in neurodegenerative diseases in general, and in Parkinson's disease (PD) in particular. Recent evidence points to the clinical value of sleep in disease progression and improving quality of life. Therefore, monitoring sleep quality in an ongoing manner at the convenience of one's home has the potential to improve clinical research and to contribute to significantly better personalized treatment. Further, precise mapping of sleep patterns of each patient can contribute to a better understanding of the disease, its progression and the appropriate medical treatment. Here we review selective, state-of-the-art, home-based devices for assessing sleep and sleep related disorders. We highlight the large potential as well as the main challenges. In particular, we discuss medical validity, standardization and regulatory concerns that currently impede widespread clinical adoption of existing devices. Finally, we propose a roadmap with the technological and scientific steps that are required to impact PD research and treatment.

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.

Effects of Levodopa on quality of sleep and nocturnal movements in Parkinson's Disease

BACKGROUND

Sleep disturbances are common in Parkinson's Disease (PD), with nocturnal akinesia being one of the most burdensome. Levodopa is frequently used in clinical routine to improve nocturnal akinesia, although evidence is not well proven.

METHODS

We assessed associations of Levodopa intake with quality of sleep and perception of nocturnal akinesia in three PD cohorts, using the Parkinson's Disease Sleep Scale (PDSS-2) in two cohorts and a question on nocturnal immobility in one cohort. In one cohort also objective assessment of mobility during sleep was performed, using mobile health technology.

RESULTS

In an independent analysis of all three cohorts (in total n = 1124 PD patients), patients taking Levodopa CR reported a significantly higher burden by nocturnal akinesia than patients without Levodopa. Higher Levodopa intake and MDS-UPDRS part IV scores (indicating motor fluctuations) predicted worse PDSS-2 and higher subjective nocturnal immobility scores, while disease duration and severity were not predictive. Levodopa intake was not associated with objectively changed mobility during sleep.

CONCLUSION

Our results showed an association of higher Levodopa intake with perception of worse quality of sleep and nocturnal immobility in PD, indicating that Levodopa alone might not be suitable to improve subjective feeling of nocturnal akinesia in PD. In contrast, Levodopa intake was not relevantly associated with objectively measured mobility during sleep. PD patients with motor fluctuations may be particularly affected by subjective perception of nocturnal mobility. This study should motivate further pathophysiological and clinical investigations on the cause of perception of immobility during sleep in PD.

REM sleep without atonia and nocturnal body position in prediagnostic Parkinson's disease

BACKGROUND

Sleep disturbances are features of Parkinson's disease (PD), that can already occur before PD diagnosis. The most investigated prodromal PD sleep disorder is REM sleep behavior disorder (RBD). The relation between other polysomnographic (PSG) alterations and the prediagnostic stages of PD, however, is less clear.

METHODS

We performed a retrospective case-control study to characterize polysomnographic alterations in PD and prediagnostic PD. We included 63 PD subjects (33 subjects that underwent a video-PSG before PD diagnosis [13 with and 20 without RBD] and 30 subjects that underwent a PSG after PD diagnosis) and 30 controls. PSGs were analyzed for sleep stages, different RSWA variables, body position, arousals, periodic limb movements, and REM density.

RESULTS

Higher subscores of all RSWA variables were observed in subjects with PD and prediagnostic PD (with and without RBD). Total RSWA, tonic RSWA and chin RSWA severity were significant predictors for all PD and prediagnostic PD groups. Our study also shows a higher percentage of nocturnal supine body position in all PD and prediagnostic PD groups. Supine body position percentage is the highest in the PD group and has a positive correlation with time since diagnosis.

CONCLUSIONS

These findings suggest that increased total, tonic and chin RSWA as well as nocturnal supine body position are already present in prediagnostic PD, independently of RBD status. Prospective longitudinal studies are necessary to confirm the additional value of these PSG abnormalities as prodromal PD biomarkers.

A randomised controlled trial on effectiveness and feasibility of sport climbing in Parkinson's disease

Physical activity is of prime importance in non-pharmacological Parkinson’s disease (PD) treatment. The current study examines the effectiveness and feasibility of sport climbing in PD patients in a single-centre, randomised controlled, semi-blind trial. A total of 48 PD patients without experience in climbing (average age 64 ± 8 years, Hoehn & Yahr stage 2–3) were assigned either to participate in a 12-week sport climbing course (SC) or to attend an unsupervised physical training group (UT). The primary outcome was the improvement of symptoms on the Movement Disorder Society-Sponsored Revision of the Unified Parkinson’s Disease Rating Scale part III (MDS-UPDRS-III). Sport climbing was associated with a significant reduction of the MDS-UPDRS-III (−12.9 points; 95% CI −15.9 to −9.8), while no significant improvement was to be found in the UT (−3.0 points; 95% CI −6.0 to 0.1). Bradykinesia, rigidity and tremor subscales significantly improved in SC, but not in the unsupervised control group. In terms of feasibility, the study showed a 99% adherence of participants to climbing sessions and a drop-out rate of only 8%. No adverse events occurred. This trial provides class III evidence that sport climbing is highly effective and feasible in mildly to moderately affected PD patients.

Detecting Sensitive Mobility Features for Parkinson's Disease Stages Via Machine Learning

BACKGROUND

It is not clear how specific gait measures reflect disease severity across the disease spectrum in Parkinson's disease (PD).

OBJECTIVE

To identify the gait and mobility measures that are most sensitive and reflective of PD motor stages and determine the optimal sensor location in each disease stage.

METHODS

Cross-sectional wearable-sensor records were collected in 332 patients with PD (Hoehn and Yahr scale I-III) and 100 age-matched healthy controls. Sensors were adhered to the participant's lower back, bilateral ankles, and wrists. Study participants walked in a ~15-meter corridor for 1 minute under two walking conditions: (1) preferred, usual walking speed and (2) walking while engaging in a cognitive task (dual-task). A subgroup (n = 303, 67% PD) also performed the Timed Up and Go test. Multiple machine-learning feature selection and classification algorithms were applied to discriminate between controls and PD and between the different PD severity stages.

RESULTS

High discriminatory values were found between motor disease stages with mean sensitivity in the range 72%-83%, specificity 69%-80%, and area under the curve (AUC) 0.76-0.90. Measures from upper-limb sensors best discriminated controls from early PD, turning measures obtained from the trunk sensor were prominent in mid-stage PD, and stride timing and regularity were discriminative in more advanced stages.

CONCLUSIONS

Applying machine-learning to multiple, wearable-derived features reveals that different measures of gait and mobility are associated with and discriminate distinct stages of PD. These disparate feature sets can augment the objective monitoring of disease progression and may be useful for cohort selection and power analyses in clinical trials of PD. © 2021 International Parkinson and Movement Disorder Society.

Digital Technology in Movement Disorders: Updates, Applications, and Challenges

Purpose of Review

Digital technology affords the opportunity to provide objective, frequent, and sensitive assessment of disease outside of the clinic environment. This article reviews recent literature on the application of digital technology in movement disorders, with a focus on Parkinson’s disease (PD) and Huntington’s disease.

Recent Findings

Recent research has demonstrated the ability for digital technology to discriminate between individuals with and without PD, identify those at high risk for PD, quantify specific motor features, predict clinical events in PD, inform clinical management, and generate novel insights.

Summary

Digital technology has enormous potential to transform clinical research and care in movement disorders. However, more work is needed to better validate existing digital measures, including in new populations, and to develop new more holistic digital measures that move beyond motor features.

Shedding Light on Nocturnal Movements in Parkinson's Disease: Evidence from Wearable Technologies

In Parkinson’s disease (PD), abnormal movements consisting of hypokinetic and hyperkinetic manifestations commonly lead to nocturnal distress and sleep impairment, which significantly impact quality of life. In PD patients, these nocturnal disturbances can reflect disease-related complications (e.g., nocturnal akinesia), primary sleep disorders (e.g., rapid eye movement behaviour disorder), or both, thus requiring different therapeutic approaches. Wearable technologies based on actigraphy and innovative sensors have been proposed as feasible solutions to identify and monitor the various types of abnormal nocturnal movements in PD. This narrative review addresses the topic of abnormal nocturnal movements in PD and discusses how wearable technologies could help identify and assess these disturbances. We first examine the pathophysiology of abnormal nocturnal movements and the main clinical and instrumental tools for the evaluation of these disturbances in PD. We then report and discuss findings from previous studies assessing nocturnal movements in PD using actigraphy and innovative wearable sensors. Finally, we discuss clinical and technical prospects supporting the use of wearable technologies for the evaluation of nocturnal movements.