Viewpoint and practical recommendations from a movement disorder specialist panel on objective measurement in the clinical management of Parkinson's disease

Non-invasive device to alleviate symptoms in people living with Parkinson's: study protocol for a multicentre phase II double-blind randomised controlled trial

INTRODUCTION

Existing interventions for people with Parkinson's disease (PwP) often fall short in addressing gait disturbances and falls, impacting their quality of life. The CUE1 non-invasive medical device, along with its updated version, CUE1+, offers vibrotactile stimulation with cueing. The device shows promise in alleviating motor symptoms and reducing falls based on early user testing and a 9-week pilot study. This study aims to assess the usability, safety, tolerability and effectiveness of CUE1+ in improving Parkinson's symptoms compared with a sham device over a 12-week period.

METHODS AND ANALYSIS

This multicentre, phase II double-blind randomised controlled trial will recruit 50 PwP from Barts Health and Homerton NHS Hospitals, enrolling them at Queen Mary University of London. Participants, diagnosed with idiopathic Parkinson's, aged 18+ and providing written consent, will be randomly assigned to either the experimental group (CUE1+ device) or control group (sham device). The primary outcome is the device usability over 12 weeks. Measures include the recruitment, compliance and dropout rates, and safety/tolerability which will be collected through a participant clinical diary at baseline (week 0) and follow-up (week 13). Effectiveness will be evaluated at the same time points using movement tests (MDS-UPDRS Part III, Functional Gait Assessment, Timed Up and Go in isolation and with dual tasking and two keyboard-based typing tests-Bradykinesia Akinesia Incoordination and Digital Finger Tapping), with video recordings. Participants will wear a Parkinson's KinetiGraph wristband to monitor symptoms at home continuously for 12 weeks and collect real-world data. Patient-reported outcomes will be collected at baseline and follow-up and include MDS-UPDRS Part I, II and IV, Activity-specific Balance Scale, Pittsburgh Sleep Quality Index, Hospital Anxiety and Depression Scale, Fatigue Symptom Scale and Parkinson's Disease Questionnaire-39.

ETHICS AND DISSEMINATION

The study has received ethical approval from London-Dulwich Research Ethics Committee (reference: 23/PR/1526). Findings will be submitted for peer-reviewed publications.

TRIAL REGISTRATION NUMBER

NCT06174948.

Improving reliability of movement assessment in Parkinson's disease using computer vision-based automated severity estimation

BackgroundClinical assessments of motor symptoms rely on observations and subjective judgments against standardized scales, leading to variability due to confounders. Improving inter-rater agreement is essential for effective disease management.ObjectiveWe developed an objective rating system for Parkinson's disease (PD) that integrates computer vision (CV) and machine learning to correct potential discrepancies among raters while providing the basis for model performance to gain professional acceptance.MethodsA prospective PD cohort (n = 128) were recruited from multi-centers. Motor examination videos were recorded using an android tablet with CV-based software following the MDS-UPDRS Part-III instructions. Videos included facial, upper- and lower-limb movements, arising from a chair, standing, and walking. Fifteen certified clinicians were recruited from multi-centers. For each video, five clinicians were randomly selected to independently rate the severity of motor symptoms, validate the videos and movement variables (MovVars). Machine learning algorithms were applied for automated rating and feature importance analysis. Inter-rater agreement among human raters and the agreement between artificial intelligence (AI)-generated ratings and expert consensus were calculated.ResultsFor all validated videos (n = 1024), AI-based ratings showed an average absolute accuracy of 69.63% and an average acceptable accuracy of 98.78% against the clinician consensus. The mean absolute error between the AI-based scores and clinician consensus was 0.32, outperforming the inter-rater variability (0.65), potentially due to the combined utilization of diverse MovVars.ConclusionsThe algorithm enabled accurate video-based evaluation of mild motor symptom severity. AI-assisted assessment improved the inter-rater agreement, demonstrating the practical value of CV-based tools in screening, diagnosing, and treating movement disorders.

Wearable devices may aid the recognition of fluctuation-related pain in Parkinson's disease-An exploratory, cross-sectional analysis of two prospective observational studies

Fluctuation-related pain (FRP) affects more than one third of people with Parkinson's disease (PwP, PD) and has a harmful effect on health-related quality of life (HRQoL), but often remains under-reported by patients and neglected by clinicians. The National Institute for Health and Care Excellence (NICE) recommends The Parkinson KinetiGraphTM (the PKGTM) for remote monitoring of motor symptoms. We investigated potential links between the PKGTM-obtained parameters and clinical rating scores for FRP in PwP in an exploratory, cross-sectional analysis of two prospective studies: "The Non-motor International Longitudinal, Real-Life Study in PD-NILS" and "An observational-based registry of baseline PKG™ in PD-PKGReg". 63 PwP (41.3% female; age: 64.24±9.88 years; disease duration, DD: 6.83±5.63 years; Hoehn and Yahr Stage, H&Y: 2 (1-4); Levodopa Equivalent Daily Dose 535 (0-3230) mg) were included. PwP with FRP (n = 23) had longer DD (8.88 (1.29-19.05) vs. 3.16 (0.34-28.92), p = 0.001), higher severity of motor symptoms (H&Y 3 (1-4) vs. 2 (1-4), p = 0.015; SCOPA Motor total score 21.35±10.19 vs. 13.65±8.99, p = 0.003), more dyskinesia (SCOPA Motor Item 18 ≥1 60.9% vs. 7.5%, p<0.001), and worse HRQoL (PDQ-8 Total Score 10.74±5.98 vs. 6.78±5.13, p = 0.007) then PwP without FRP (n = 40). In the multivariate logistic regression, after the adjustment for DD, H&Y and SCOPA-Motor total score, the presence of FRP was significantly associated with the PKGTM-derived Fluctuation-dyskinesia score (Exp (B) = 1.305, 95% CI for Exp (B) 1.012-1.683, p = 0.040) and the Bradykinesia score (Exp (B) = 0.917, 95% CI for Exp (B) 0.842-0.999, p = 0.048). The PKGTM system may potentially advance the way we screen for, assess, and treat FRP in clinical practice.

Motor Efficacy of Subcutaneous DIZ102, Intravenous DIZ101 or Intestinal Levodopa/Carbidopa Infusion

BACKGROUND

It has been suggested that carbidopa at high blood concentrations may counter the therapeutic effect of levodopa in Parkinson's disease by entering the brain and blocking central levodopa conversion to dopamine. We previously demonstrated equivalent plasma levodopa concentration in patients with Parkinson's disease during 16 h of (1) intravenous carbidopa/levodopa (DIZ101) infusion, (2) subcutaneous carbidopa/levodopa (DIZ102) infusion or (3) intestinal carbidopa/levodopa gel infusion. Plasma levels of carbidopa were however approximately four times higher with DIZ101 and DIZ102 than with LCIG, and higher than those usually observed with oral levodopa/carbidopa.

OBJECTIVES

To investigate if high carbidopa blood concentrations obtained with parenteral levodopa/carbidopa (ratio 8:1) counter the effect of levodopa on motor symptoms.

METHODS

Eighteen patients with advanced Parkinson's disease were administered DIZ101, DIZ102, and intestinal levodopa/carbidopa gel for 16 h on different days in randomized order. Video recordings of a subset of the motor examination in the Unified Parkinson's Disease Rating Scale (UPDRS) were evaluated by raters blinded for treatment and time. Motor function was also measured using a wrist-worn device monitoring bradykinesia, dyskinesia, and tremor (Parkinson KinetiGraph).

RESULTS

There was no tendency for poorer levodopa effect with DIZ101 or DIZ102 as compared to LCIG.

CONCLUSION

Although DIZ101 or DIZ102 causes approximately four times higher plasma carbidopa levels than LCIG, patients responded equally well to all treatments. The results do not indicate that high plasma carbidopa levels hamper the motor efficacy of levodopa.

Sensor-Based Quantification of MDS-UPDRS III Subitems in Parkinson's Disease Using Machine Learning

Wearable sensors could be beneficial for the continuous quantification of upper limb motor symptoms in people with Parkinson's disease (PD). This work evaluates the use of two inertial measurement units combined with supervised machine learning models to classify and predict a subset of MDS-UPDRS III subitems in PD. We attached the two compact wearable sensors on the dorsal part of each hand of 33 people with PD and 12 controls. Each participant performed six clinical movement tasks in parallel with an assessment of the MDS-UPDRS III. Random forest (RF) models were trained on the sensor data and motor scores. An overall accuracy of 94% was achieved in classifying the movement tasks. When employed for classifying the motor scores, the averaged area under the receiver operating characteristic values ranged from 68% to 92%. Motor scores were additionally predicted using an RF regression model. In a comparative analysis, trained support vector machine models outperformed the RF models for specific tasks. Furthermore, our results surpass the literature in certain cases. The methods developed in this work serve as a base for future studies, where home-based assessments of pharmacological effects on motor function could complement regular clinical assessments.

Overview on wearable sensors for the management of Parkinson's disease

Parkinson's disease (PD) is affecting about 1.2 million patients in Europe with a prevalence that is expected to have an exponential increment, in the next decades. This epidemiological evolution will be challenged by the low number of neurologists able to deliver expert care for PD. As PD is better recognized, there is an increasing demand from patients for rigorous control of their symptoms and for therapeutic education. In addition, the highly variable nature of symtoms between patients and the fluctuations within the same patient requires innovative tools to help doctors and patients monitor the disease in their usual living environment and adapt treatment in a more relevant way. Nowadays, there are various body-worn sensors (BWS) proposed to monitor parkinsonian clinical features, such as motor fluctuations, dyskinesia, tremor, bradykinesia, freezing of gait (FoG) or gait disturbances. BWS have been used as add-on tool for patients' management or research purpose. Here, we propose a practical anthology, summarizing the characteristics of the most used BWS for PD patients in Europe, focusing on their role as tools to improve treatment management. Consideration regarding the use of technology to monitor non-motor features is also included. BWS obviously offer new opportunities for improving management strategy in PD but their precise scope of use in daily routine care should be clarified.

Identification and quantitative assessment of motor complications in Parkinson's disease using the Parkinson's KinetiGraph™

Introduction

Effective management and therapies for the motor complications of Parkinson's disease (PD) require appropriate clinical evaluation. The Parkinson's KinetiGraph™ (PKG) is a wearable biosensor system that can record the motion characteristics of PD objectively and remotely.

Objective

The study aims to investigate the value of PKG in identifying and quantitatively assessing motor complications including motor fluctuations and dyskinesia in the Chinese PD population, as well as the correlation with the clinical scale assessments.

Methods

Eighty-four subjects with PD were recruited and continuously wore the PKG for 7 days. Reports with 7-day output data were provided by the manufacturer, including the fluctuation scores (FS) and dyskinesia scores (DKS). Specialists in movement disorders used the Movement Disorder Society-Unified Parkinson's Disease Rating Scale-IV (MDS-UPDRS IV), the wearing-off questionnaire 9 (WOQ-9), and the unified dyskinesia rating scale (UDysRS) for the clinical assessment of motor complications. Spearman correlation analyses were used to evaluate the correlation between the FS and DKS recorded by the PKG and the clinical scale assessment results. Receiver operating characteristic (ROC) curves were generated to analyze the sensitivity and specificity of the FS and DKS scores in the identification of PD motor complications.

Results

The FS was significantly positively correlated with the MDS-UPDRS IV motor fluctuation (items 4.3-4.5) scores (r = 0.645, p < 0.001). ROC curve analysis showed a maximum FS cut-off value of 7.5 to identify motor fluctuation, with a sensitivity of 74.3% and specificity of 87.8%. The DKS was significantly positively correlated with the UDysRS total score (r = 0.629, p < 0.001) and the UDysRS III score (r = 0.634, p < 0.001). ROC curve analysis showed that the maximum DKS cut-off value for the diagnosis of dyskinesia was 0.7, with a sensitivity of 83.3% and a specificity of 83.3%.

Conclusion

The PKG assessment of motor complications in the PD population analyzed in this study has a significant correlation with the clinical scale assessment, high sensitivity, and high specificity. Compared with clinical evaluations, PKG can objectively, quantitatively, and remotely identify and assess motor complications in PD, providing a good objective recording for managing motor complications.

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.

Levodopa-Induced Dyskinesias in Parkinson's Disease: An Overview on Pathophysiology, Clinical Manifestations, Therapy Management Strategies and Future Directions

Since its first introduction, levodopa has become the cornerstone for the treatment of Parkinson's disease and remains the leading therapeutic choice for motor control therapy so far. Unfortunately, the subsequent appearance of abnormal involuntary movements, known as dyskinesias, is a frequent drawback. Despite the deep knowledge of this complication, in terms of clinical phenomenology and the temporal relationship during a levodopa regimen, less is clear about the pathophysiological mechanisms underpinning it. As the disease progresses, specific oscillatory activities of both motor cortical and basal ganglia neurons and variation in levodopa metabolism, in terms of the dopamine receptor stimulation pattern and turnover rate, underlie dyskinesia onset. This review aims to provide a global overview on levodopa-induced dyskinesias, focusing on pathophysiology, clinical manifestations, therapy management strategies and future directions.

Clinical Evaluation in Parkinson's Disease: Is the Golden Standard Shiny Enough?

Parkinson's disease (PD) has become the second most common neurodegenerative condition following Alzheimer's disease (AD), exhibiting high prevalence and incident rates. Current care strategies for PD patients include brief appointments, which are sparsely allocated, at outpatient clinics, where, in the best case scenario, expert neurologists evaluate disease progression using established rating scales and patient-reported questionnaires, which have interpretability issues and are subject to recall bias. In this context, artificial-intelligence-driven telehealth solutions, such as wearable devices, have the potential to improve patient care and support physicians to manage PD more effectively by monitoring patients in their familiar environment in an objective manner. In this study, we evaluate the validity of in-office clinical assessment using the MDS-UPDRS rating scale compared to home monitoring. Elaborating the results for 20 patients with Parkinson's disease, we observed moderate to strong correlations for most symptoms (bradykinesia, rest tremor, gait impairment, and freezing of gait), as well as for fluctuating conditions (dyskinesia and OFF). In addition, we identified for the first time the existence of an index capable of remotely measuring patients' quality of life. In summary, an in-office examination is only partially representative of most PD symptoms and cannot accurately capture daytime fluctuations and patients' quality of life.

Symptoms assessment and decision to treat patients with advanced Parkinson's disease based on wearables data

Body-worn sensors (BWS) could provide valuable information in the management of Parkinson's disease and support therapeutic decisions based on objective monitoring. To study this pivotal step and better understand how relevant information is extracted from BWS results and translated into treatment adaptation, eight neurologists examined eight virtual cases composed of basic patient profiles and their BWS monitoring results. Sixty-four interpretations of monitoring results and the subsequent therapeutic decisions were collected. Relationship between interrater agreements in the BWS reading and the severity of symptoms were analyzed via correlation studies. Logistic regression was used to identify associations between the BWS parameters and suggested treatment modifications. Interrater agreements were high and significantly associated with the BWS scores. Summarized BWS scores reflecting bradykinesia, dyskinesia, and tremor predicted the direction of treatment modifications. Our results suggest that monitoring information is robustly linked to treatment adaptation and pave the way to loop systems able to automatically propose treatment modifications from BWS recordings information.

Measurement of bradykinesia and chorea in Huntington's Disease using ambulatory monitoring

Objectives

The feasibility of measuring bradykinesia and chorea in Huntington's Disease using a wearable sensor system (Parkinson's Kinetigraph: PKG) developed for measuring bradykinesia and dyskinesia in Parkinson's Disease was assessed.

Methods

Unified Huntington's Disease Rating Scales (UHDRS) and a PKG were obtained for 25 people with Huntington's Disease. Bradykinesia and Chorea Score were derived from relevant sub-scores of the UHDRS and compared with the PKG's bradykinesia and dyskinesia scores. The PKG's daytime sleepiness score was also used.

Results

There was good correlation between Chorea Scores and the PKG's dyskinesia score (Pearson's ρ = 0.66). Correlation between the Bradykinesia Scores and the PKG's bradykinesia score was also good (Pearson's ρ = 0.51) in cases whose PKG scores were in the normal or bradykinetic range. The PKG's bradykinesia score of 23, which is in the higher range of control subjects, separated participants into those with Independence Score ≥ 80 or < 80 and a Functional Assessment (FAS) score ≥ 18 or < 18. The PKG's daytime sleep score was high in 44 % of participants, whose average time asleep was 21 % compared to 1.6 % in participants with a normal sleep index. Participants with high sleep scores were significantly more likely to have low Independence and TFC scores.

Conclusions

Measures of bradykinesia and dyskinesia from clinical scales have acceptable correlations with those from the PKG. Continuous monitoring provides information about daytime sleep, which was associated with lower functional status. Further studies and larger sample sizes are required to confirm these findings and the utility of this measure in Huntington's Disease.

Clinical correlates of movement disorders in adult Niemann-Pick type C patients measured via a Personal KinetiGraph

Background

Niemann-Pick type C (NPC) is an autosomal recessive progressive neurodegenerative disorder caused by mutations in the NPC1 or NPC2 genes. Patients with this disorder have variable phenotypic presentations that often include neuropsychiatric manifestations, cognitive decline, and movement disorders. There is considerable interpatient variation in movement disorders, with limited quantitative measurements describing the movements observed. Objective measurements using wearable sensors provide clinically applicable monitoring of patients with Parkinson’s disease, and hence may be utilized in patients with NPC.

Objective

To explore the relationship between objective measurements of movement obtained via the use of the Personal KinetiGraph (PKG) with the clinical information obtained via questionnaires and clinical rating tools of patients with Niemann-Pick type C.

Methods

Twelve patients with Niemann-Pick type C were recruited who wore the PKG for 6 days during regular activities. A 6-day output was provided by the manufacturer, which provided bradykinesia (BK) and dyskinesia (DK) scores. BK and DK scores were further divided into their interquartile ranges. A fluctuation score (FDS), percentage time immobile (PTI), and percent time with tremors (PTT) were also provided. Clinical assessments included Abnormal Involuntary Movement Scale (AIMS), Epworth Sleepiness Score (ESS), Falls, Neuropsychiatric Unit Assessment Tool (NUCOG), Parkinson’s disease questionnaire (PDQ), and modified Unified Parkinson’s Disease Rating Scale (UPDRS) which were performed over telehealth within 2 weeks of PKG use. Pearson’s correlation analyses were utilized to explore the relationship between DK and BK quartiles and clinical measures.

Results

We found bradykinesia to be a feature among this cohort of patients, with a median BKS of 22.0 (7.4). Additionally, PTI scores were elevated at 4.9 (8.2) indicating elevated daytime sleepiness. Significant correlations were demonstrated between BK25 and Falls (r =  − 0.74, 95% CI = [− 0.95, − 0.08]), BK50 and Falls (r =  − 0.79, 95% CI = [− 0.96, − 0.19]), and BK75 and Falls (r =  − 0.76, 95% CI = [− 0.95, − 0.11]). FDS correlated with PDQ (r =  − 0.7, 95% CI = [− 0.92, − 0.18]), UPDRS IV (r =  − 0.65, 95% CI = [− 0.90, − 0.09]), UPDRS (r =  − 0.64, 95% CI = [− 0.9, − 0.06]), and AIMS (r =  − 0.96, 95% CI = [− 0.99, − 0.49]). DK25 in comparison with NUCOG-A (r = 0.72, 95% CI = [0.17, 0.93]) and DK75 in comparison with NUCOG (r = 0.64, 95% CI = [0.02, 0.91]) and NUCOG-A (r = 0.63, 95% CI = [0.01, 0.90]) demonstrated significant correlations. Additionally, duration of illness in comparison with PTI (r = 0.72, 95% CI = [0.22, 0.92]) demonstrated significance.

Conclusions

Utilization of PKG measures demonstrated that bradykinesia is under recognized among NPC patients, and the bradykinetic patients were less likely to report concerns regarding falls. Additionally, the FDS rather than the DKS is sensitive to the abnormal involuntary movements of NPC—reflecting a differing neurobiology of this chorea compared to levodopa-induced dyskinesias. Furthermore, dyskinetic individuals performed better in cognitive assessments of attention which may indicate an earlier timepoint within disease progression.

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.

Sensor Measurements Can Characterize Fluctuations and Wearing Off in Parkinson’s Disease and Guide Therapy to Improve Motor, Non-motor and Quality of Life Scores

Objectives

The aim was to examine the role of sensor measurement in identifying and managing fluctuations in bradykinesia of Parkinson’s Disease.

Method

Clinical scales and data from wearable sensors obtained before and after optimization of treatment from 107 participants who participated in a previous study was used. Fluctuators were identified by a levodopa response or wearing off in their sensor data and were subdivided according to whether the sensor’s bradykinesia scores were in target range, representing acceptable bradykinesia for part of the dose (Controlled Fluctuator: n = 22) or above target for the whole dose period (Uncontrolled Fluctuator; n = 28). Uncontrolled Non-fluctuators (n = 24) were cases without a levodopa response or wearing-off and sensor bradykinesia scores above target throughout the day (un-controlled). Controlled Non-fluctuators (n = 33) were below target throughout the day (controlled) and used as a reference for good control (MDS-UPDRS III = 33 ± 8.6 and PDQ39 = 28 ± 18).

Results

Treating Fluctuators significantly improved motor and quality of life scores. Converting fluctuators into Controlled Non-fluctuators significantly improved motor, non-motor and quality of life scores and a similar but less significant improvement was obtained by conversion to a Controlled Fluctuator. There was a significantly greater likelihood of achieving these changes when objective measurement was used to guide management.

Conclusions

The sensor’s classification of fluctuators bore a relation to severity of clinical scores and treatment of fluctuation improved clinical scores. The sensor measurement aided in recognizing and removing fluctuations with treatment and resulted in better clinical scores, presumably by assisting therapeutic decisions.

A cross-sectional study of knowledge and practices in the management of patients with Parkinson’s disease amongst public practice-based general practitioners and geriatricians

Background

As most patients are likely to first interface with their community general practitioner (GP) or geriatrician for chronic healthcare conditions, these non-neurologists practitioners are well-placed to diagnose, initiate treatment in symptomatic Parkinson’s disease (PD) patients, and provide regular and timely management of their PD. However, current studies suggest that the role of the GP and geriatrician in providing holistic care for PD patients may be limited by factors such as patient perceptions, and a lack of knowledge base in the quality measures of care. This paper aims to better understand the different management styles between GPs and geriatricians practicing in public institutions in Singapore, qualify the difficulties they face in providing patient-centric care for PD patients, and identify any gaps in quality measures of care.

Methods

A questionnaire was completed anonymously by GPs (n = 43) and geriatricians (n = 33) based at public institutions, on a voluntary basis before a compulsory didactic teaching on PD. Questions were modelled after quality measures set out by the American Academy of Neurology, specifically eliciting information on falls, non-motor symptoms, exercise regime and medication-related symptoms. “PD management practices and styles” questions were answered by the respondents on a 4-point Likert scale.

Results

Geriatricians spent more time in consult with PD patients compared with GPs (median [Q1-Q3] = 20 [15–30] vs 10 [10–15] minutes, p <  0.001). Geriatricians were more comfortable initiating PD medications than GPs (OR = 11.8 [95% CI: 3.54–39.3], p <  0.001), independent of gender, years of practice and duration of consult. Comfort in initiating dopamine replacement therapy (OR 1.06 [1.00–1.36], p = 0.07; aOR = 1.14 [1.02–1.26], p = 0.02) also increased with physician’s years of practice. Unfamiliarity with the types and/or doses of the medications was the most cited barrier faced by GPs (76.7%). Geriatricians were more likely than GPs to ask about falls (100% vs 86.0%, p = 0.025), non-motor symptoms (75.8% vs 53.5%, p = 0.049) and the patient’s regular physical activities (72.7% vs 41.9%, p = 0.01).

Conclusions

This study identified key patterns in the management practices and styles of non-neurologists physicians, and identified gaps in current practice. Our data suggests that interventions directed at education on PD medication prescriptions and provision of patient PD education, creation of best clinical practice guidelines, and accreditation by national bodies may instil greater confidence in practitioners to initiate and continue patient-centric PD care. A longer consultation duration with PD patients should be considered to allow physicians to get a greater scope of the patient’s needs and better manage them.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-07503-7.

Technology-Based Neurorehabilitation in Parkinson’s Disease—A Narrative Review

This narrative review provides a brief overview of the current literature on technology-based interventions for the neurorehabilitation of persons with Parkinson’s disease (PD). The role of brain–computer interfaces, exergaming/virtual-reality-based exercises, robot-assisted therapies and wearables is discussed. It is expected that technology-based neurorehabilitation will gain importance in the management of PD patients, although it is often not clear yet whether this approach is superior to conventional therapies. High-intensity technology-based neurorehabilitation may hold promise with respect to neuroprotective or neurorestorative actions in PD. Overall, more research is required in order to obtain more data on the feasibility, efficacy and safety of technology-based neurorehabilitation in persons with PD.

Rapid Dynamic Naturalistic Monitoring of Bradykinesia in Parkinson's Disease Using a Wrist-Worn Accelerometer

Motor fluctuations in Parkinson’s disease are characterized by unpredictability in the timing and duration of dopaminergic therapeutic benefits on symptoms, including bradykinesia and rigidity. These fluctuations significantly impair the quality of life of many Parkinson’s patients. However, current clinical evaluation tools are not designed for the continuous, naturalistic (real-world) symptom monitoring needed to optimize clinical therapy to treat fluctuations. Although commercially available wearable motor monitoring, used over multiple days, can augment neurological decision making, the feasibility of rapid and dynamic detection of motor fluctuations is unclear. So far, applied wearable monitoring algorithms are trained on group data. In this study, we investigated the influence of individual model training on short timescale classification of naturalistic bradykinesia fluctuations in Parkinson’s patients using a single-wrist accelerometer. As part of the Parkinson@Home study protocol, 20 Parkinson patients were recorded with bilateral wrist accelerometers for a one hour OFF medication session and a one hour ON medication session during unconstrained activities in their own homes. Kinematic metrics were extracted from the accelerometer data from the bodyside with the largest unilateral bradykinesia fluctuations across medication states. The kinematic accelerometer features were compared over the 1 h duration of recording, and medication-state classification analyses were performed on 1 min segments of data. Then, we analyzed the influence of individual versus group model training, data window length, and total number of training patients included in group model training, on classification. Statistically significant areas under the curves (AUCs) for medication induced bradykinesia fluctuation classification were seen in 85% of the Parkinson patients at the single minute timescale using the group models. Individually trained models performed at the same level as the group trained models (mean AUC both 0.70, standard deviation respectively 0.18 and 0.10) despite the small individual training dataset. AUCs of the group models improved as the length of the feature windows was increased to 300 s, and with additional training patient datasets. We were able to show that medication-induced fluctuations in bradykinesia can be classified using wrist-worn accelerometry at the time scale of a single minute. Rapid, naturalistic Parkinson motor monitoring has the clinical potential to evaluate dynamic symptomatic and therapeutic fluctuations and help tailor treatments on a fast timescale.

Adaptive, personalized closed-loop therapy for Parkinson's disease: biochemical, neurophysiological, and wearable sensing systems

INTRODUCTION

Motor complication management is one of the main unmet needs in Parkinson's disease patients.

AREAS COVERED

Among the most promising emerging approaches for handling motor complications in Parkinson's disease, adaptive deep brain stimulation strategies operating in closed-loop have emerged as pivotal to deliver sustained, near-to-physiological inputs to dysfunctional basal ganglia-cortical circuits over time. Existing sensing systems that can provide feedback signals to close the loop include biochemical-, neurophysiological- or wearable-sensors. Biochemical sensing allows to directly monitor the pharmacokinetic and pharmacodynamic of antiparkinsonian drugs and metabolites. Neurophysiological sensing relies on neurotechnologies to sense cortical or subcortical brain activity and extract real-time correlates of symptom intensity or symptom control during DBS. A more direct representation of the symptom state, particularly the phenomenological differentiation and quantification of motor symptoms, can be realized via wearable sensor technology.

EXPERT OPINION

Biochemical, neurophysiologic, and wearable-based biomarkers are promising technological tools that either individually or in combination could guide adaptive therapy for Parkinson's disease motor symptoms in the future.

Therapeutic maps for a sensor-based evaluation of deep brain stimulation programming

Programming in deep brain stimulation (DBS) is a labour-intensive process for treating advanced motor symptoms. Specifically for patients with medication-refractory tremor in multiple sclerosis (MS). Wearable sensors are able to detect some manifestations of pathological signs, such as intention tremor in MS. However, methods are needed to visualise the response of tremor to DBS parameter changes in a clinical setting while patients perform the motor task finger-to-nose. To this end, we attended DBS programming sessions of a MS patient and intention tremor was effectively quantified by acceleration amplitude and frequency. A new method is introduced which results in the generation of therapeutic maps for a systematic review of the programming procedure in DBS. The maps visualise the combination of tremor acceleration power, clinical rating scores, total electrical energy delivered to the brain and possible side effects. Therapeutic maps have not yet been employed and could lead to a certain degree of standardisation for more objective decisions about DBS settings. The maps provide a base for future research on visualisation tools to assist physicians who frequently encounter patients for DBS therapy.

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.

Multicentre, randomised, single-blind, parallel group trial to compare the effectiveness of a Holter for Parkinson's symptoms against other clinical monitoring methods: study protocol

INTRODUCTION

In recent years, multiple studies have aimed to develop and validate portable technological devices capable of monitoring the motor complications of Parkinson's disease patients (Parkinson's Holter). The effectiveness of these monitoring devices for improving clinical control is not known.

METHODS AND ANALYSIS

This is a single-blind, cluster-randomised controlled clinical trial. Neurologists from Spanish health centres will be randomly assigned to one of three study arms (1:1:1): (a) therapeutic adjustment using information from a Parkinson's Holter that will be worn by their patients for 7 days, (b) therapeutic adjustment using information from a diary of motor fluctuations that will be completed by their patients for 7 days and (c) therapeutic adjustment using clinical information collected during consultation. It is expected that 162 consecutive patients will be included over a period of 6 months.The primary outcome is the efficiency of the Parkinson's Holter compared with traditional clinical practice in terms of Off time reduction with respect to the baseline (recorded through a diary of motor fluctuations, which will be completed by all patients). As secondary outcomes, changes in variables related to other motor complications (dyskinesia and freezing of gait), quality of life, autonomy in activities of daily living, adherence to the monitoring system and number of doctor-patient contacts will be analysed. The noninferiority of the Parkinson's Holter against the diary of motor fluctuations in terms of Off time reduction will be studied as the exploratory objective.Ethics and dissemination approval for this study has been obtained from the Hospital Universitari de Bellvitge Ethics Committee. The results of this study will inform the practical utility of the objective information provided by a Parkinson's Holter and, therefore, the convenience of adopting this technology in clinical practice and in future clinical trials. We expect public dissemination of the results in 2022.

TRIAL REGISTRATION

NCT04176302; https://clinicaltrials.gov/show/NCT04176302.

Parkinson's Disease: Personalized Pathway of Care for Device-Aided Therapies (DAT) and the Role of Continuous Objective Monitoring (COM) Using Wearable Sensors

Parkinson’s disease (PD) is a chronic, progressive neurological disorder and the second most common neurodegenerative condition. Advanced PD is complicated by erratic gastric absorption, delayed gastric emptying in turn causing medication overload, and hence the emergence of motor and non-motor fluctuations and dyskinesia, which is initially predictable and then becomes unpredictable. As the patient progresses to the advanced stage, advanced Parkinson’s disease (APD) is characterized by refractory motor and non motor fluctuations, unpredictable OFF periods, and troublesome dyskinesias. The management of APD is a complex affair. There is growing recognition that GI dysfunction is common in PD, with virtually the entire GI system (the upper and lower GI tracts) causing problems from dribbling to defecation. The management of PD should focus on personalized care addressing both motor and non-motor symptoms, ideally including not only dopamine replacement but also associated non-dopaminergic circuits, particularly focusing on noradrenergic, serotonergic, and cholinergic therapies bypassing the gastrointestinal tract (GIT) by infusion or device-aided therapies (DAT), including levodopa–carbidopa intestinal gel infusion, apomorphine subcutaneous infusion, and deep brain stimulation, which are available in many countries for the management of the advanced stage of Parkinson’s disease (APD). The PKG (KinetiGrap) can be used as a continuous objective monitoring (COM) aid, as a screening tool to help to identify advanced PD (APD) patients suitable for DAT, and can thus improve clinical outcomes.

A method for measuring time spent in bradykinesia and dyskinesia in people with Parkinson's disease using an ambulatory monitor

Background

Fluctuations in motor function in Parkinson’s Disease (PD) are frequent and cause significant disability. Frequently device assisted therapies are required to treat them. Currently, fluctuations are self-reported through diaries and history yet frequently people with PD do not accurately identify and report fluctuations. As the management of fluctuations and the outcomes of many clinical trials depend on accurately measuring fluctuations a means of objectively measuring time spent with bradykinesia or dyskinesia would be important. The aim of this study was to present a system that uses wearable sensors to measure the percentage of time that bradykinesia or dyskinesia scores are above a target as a means for assessing levels of treatment and fluctuations in PD.

Methods

Data in a database of 228 people with Parkinson’s Disease and 157 control subjects, who had worn the Parkinson’s Kinetigraph ((PKG, Global Kinetics Corporation™, Australia) and scores from the Unified Parkinson’s Disease Rating Scale (UPDRS) and other clinic scales were used. The PKG’s provided score for bradykinesia and dyskinesia every two minutes and these were compared to a previously established target range representing a UPDRS III score of 35. The proportion of these scores above target over the 6 days that the PKG was worn were used to derive the percent time in bradykinesia (PTB) and percent time in dyskinesia (PTD). As well, a previously describe algorithm for estimating the amplitude of the levodopa response was used to determine whether a subject was a fluctuator or non-fluctuator.

Results

Using this approach, a normal range of PTB and PTD based on Control subject was developed. The level of PTB and PTD experienced by people with PD was compared with their levels of fluctuation. There was a correlation (Pearson’s ρ = 0.4) between UPDRS II scores and PTB: the correlation between Parkinson Disease Questionnaire scores and UPDRS Total scores and PTB and slightly lower. PTB and PTD fell in response to treatment for bradykinesia or dyskinesia (respectively) with greater sensitivity than clinical scales.

Conclusions

This approach provides an objective assessment of the severity of fluctuations in Parkinson’s Disease that could be used in in clinical trials and routine care.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12984-021-00905-4.

Does Information from the Parkinson KinetiGraph™ (PKG) Influence the Neurologist's Treatment Decisions?-An Observational Study in Routine Clinical Care of People with Parkinson's Disease

Management of Parkinson's disease traditionally relies solely on clinical assessment. The PKG objectively measures affected persons' movements in daily life. The present study evaluated how often PKG data changed treatment decisions in routine clinical care and to what extent the clinical assessment and the PKG interpretation differed. PKG recordings were performed before routine visits. The neurologist first made a clinical assessment without reviewing the PKG. Signs and symptoms were recorded, and a treatment plan was documented. Afterward, the PKG was evaluated. Then, the neurologist decided whether to change the initial treatment plan or not. PKG review resulted in a change in the initial treatment plan in 21 of 66 participants (31.8%). The clinical assessment and the PKG review differed frequently, mainly regarding individual overall presence of motor problems (67%), profile of bradykinesia/wearing off (79%), dyskinesia (35%) and sleep (55%). PKG improved the dialogue with the participant in 88% of cases. PKG and clinical variables were stable when they were repeated after 3-6 months. In conclusion, PKG information changes treatment decisions in nearly a third of people with Parkinson's disease in routine care. Standard clinical assessment and PKG evaluation are often non-identical. Objective measurements in people living with Parkinson's disease can add therapeutically relevant information.

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

Background: Several small-scale studies have shown that motor performance in Parkinson’s disease (PD) fluctuates throughout the day. Studies specifically focusing on de novo patients are, however, lacking. Objective: To evaluate the effect of clock time on motor performance in de novo drug-naïve patients with PD. Methods: We retrieved MDS-UPDRS III scores for 421 de novo PD patients from the PPMI cohort and stratified them into three groups based on time of assessment: group 1) 7:00–10:00; group 2) 10:00–13:00, and group 3) 13:00–18:00. Groups were compared using Kruskal-Wallis test and results corrected for multiple testing. In addition, we obtained 27 wearable sensor reports, objectively capturing bradykinesia scores in a home setting over a 6-day continuous period, in 12 drug-naïve patients from the Parkinson’s Kinetigraph Registry held at King’s College Hospital London. Time spent in severe bradykinesia scores were broken down into five daytime (06:00–21:00) three-hourly epochs and scores compared using the Friedman test. Results: There were no group differences in demographic or other clinical variables for the cross-sectional analysis. MDS-UPDRS III total scores worsened significantly during the course of the day (median 18 (group 1); 20 (group 2); and 23 (group 3); p = 0.001). In the longitudinal wearable sensor cohort, diurnal variations were present in percentage of time spent in severe bradykinesia (p < 0.001) with the lowest percentage during the 09:00–12:00 epoch (69.56±16.68%), when most patients are awake and start daily activity, and the highest percentage during the 18:00–21:00 epoch (73.58±16.35%). Conclusion: This exploratory study shows the existence of a diurnal pattern of motor function in patients with de novo PD. The results obtained were corroborated by objective measurements in a small longitudinal cohort confirming a similar diurnal motor score variation.

Wearables als unterstützendes Tool für den Paradigmenwechsel in der Versorgung von Parkinson Patienten

Tragbare Sensoren – „Wearables“ – eignen sich, Funktionsstörungen bei Parkinson Patienten zu erheben und werden zur Prävention, Prädiktion, Diagnostik und Therapieunterstützung genutzt. In der Forschung erhöhen sie die Reliabilität der erhobenen Daten und stellen bessere Studien-Endpunkte dar, als die herkömmlichen, subjektiven und wenig quantitativen Rating- und Selbstbeurteilungsskalen. Untersucht werden motorische Symptome wie Tremor, Bradykinese und Gangstörungen und auch nicht motorische Symptome. In der Home-Monitoringanwendung kann der Ist-Zustand des Patienten im realen Leben untersucht werden, die Therapie überwacht, die Adhärenz verbessert und die Compliance überprüft werden. Zusätzlich können Wearables interventionell zur Verbesserung von Symptomen eingesetzt werden wie z. B. Cueing, Gamification oder Coaching. Der Transfer von Laborbedingungen in den häuslichen Alltag ist eine medizinisch-technische Herausforderung. Optimierte Versorgungsmodelle müssen entwickelt werden und der tatsächliche Nutzen für den individuellen Patienten in weiteren Studien belegt werden.

A Long-Term, Real-Life Parkinson Monitoring Database Combining Unscripted Objective and Subjective Recordings

Accurate real-life monitoring of motor and non-motor symptoms is a challenge in Parkinson’s disease (PD). The unobtrusive capturing of symptoms and their naturalistic fluctuations within or between days can improve evaluation and titration of therapy. First-generation commercial PD motion sensors are promising to augment clinical decision-making in general neurological consultation, but concerns remain regarding their short-term validity, and long-term real-life usability. In addition, tools monitoring real-life subjective experiences of motor and non-motor symptoms are lacking. The dataset presented in this paper constitutes a combination of objective kinematic data and subjective experiential data, recorded parallel to each other in a naturalistic, long-term real-life setting. The objective data consists of accelerometer and gyroscope data, and the subjective data consists of data from ecological momentary assessments. Twenty PD patients were monitored without daily life restrictions for fourteen consecutive days. The two types of data can be used to address hypotheses on naturalistic motor and/or non-motor symptomatology in PD.

A blinded, controlled trial of objective measurement in Parkinson's disease

Medical conditions with effective therapies are usually managed with objective measurement and therapeutic targets. Parkinson’s disease has effective therapies, but continuous objective measurement has only recently become available. This blinded, controlled study examined whether management of Parkinson’s disease was improved when clinical assessment and therapeutic decisions were aided by objective measurement. The primary endpoint was improvement in the Movement Disorder Society-United Parkinson’s Disease Rating Scale’s (MDS-UPDRS) Total Score. In one arm, objective measurement assisted doctors to alter therapy over successive visits until objective measurement scores were in target. Patients in the other arm were conventionally assessed and therapies were changed until judged optimal. There were 75 subjects in the objective measurement arm and 79 in the arm with conventional assessment and treatment. There were statistically significant improvements in the moderate clinically meaningful range in the MDS-UPDRS Total, III, IV scales in the arm using objective measurement, but not in the conventionally treated arm. These findings show that global motor and non-motor disability is improved when management of Parkinson’s disease is assisted by objective measurement.

Parkinson's disease: current assessment methods and wearable devices for evaluation of movement disorder motor symptoms - a patient and healthcare professional perspective

BACKGROUND

Parkinson's disease is the second most common long-term chronic, progressive, neurodegenerative disease, affecting more than 10 million people worldwide. There has been a rising interest in wearable devices for evaluation of movement disorder diseases such as Parkinson's disease due to the limitations in current clinic assessment methods such as Unified Parkinson's Disease Rating Scale (UPDRS) and the Hoehn and Yahr (HY) scale. However, there are only a few commercial wearable devices available, which, in addition, have had very limited adoption and implementation. This inconsistency may be due to a lack of users' perspectives in terms of device design and implementation. This study aims to identify the perspectives of healthcare professionals and patients linked to current assessment methods and to identify preferences, and requirements of wearable devices.

METHODS

This was a qualitative study using semi-structured interviews followed by focus groups. Transcripts from sessions were analysed using an inductive thematic approach.

RESULTS

It was noted that the well-known assessment process such as Unified Parkinson's Disease Rating Scale (UPDRS) was not used routinely in clinics since it is time consuming, subjective, inaccurate, infrequent and dependent on patients' memories. Participants suggested that objective assessment methods are needed to increase the chance of effective treatment. The participants' perspectives were positive toward using wearable devices, particularly if they were involved in early design stages. Patients emphasized that the devices should be comfortable, but they did not have any concerns regarding device visibility or data privacy transmitted over the internet when it comes to their health. In terms of wearing a monitor, the preferable part of the body for all participants was the wrist. Healthcare professionals stated a need for an economical solution that is easy to interpret. Some design aspects identified by patients included clasps, material choice, and form factor.

CONCLUSION

The study concluded that current assessment methods are limited. Patients' and healthcare professionals' involvement in wearable devices design process has a pivotal role in terms of ultimate user acceptance. This includes the provision of additional functions to the wearable device, such as fall detection and medication reminders, which could be attractive features for patients.

Seven Solutions for Neuroprotection in Parkinson's Disease

Parkinson's disease (PD) is a neurodegenerative disorder characterized by loss of dopaminergic neurons in the substantia nigra and accumulation of iron and alpha-synuclein; it follows a characteristic pattern throughout the nervous system. Despite decades of successful preclinical neuroprotective studies, no drug has then shown efficacy in clinical trials. Considering this dilemma, we have reviewed and organized solutions of varying importance that can be exclusive or additive, and we outline approaches to help generate successful development of neuroprotective drugs for PD: (1) select patients in which the targeted mechanism is involved in the pathological process associated with the monitoring of target engagement, (2) combine treatments that target multiple pathways, (3) establish earliest interventions and develop better prodromal biomarkers, (4) adopt rigorous methodology and specific disease-relevant designs for disease-modifying clinical trials, (5) customize drug with better brain biodistribution, (6) prioritize repurposed drugs as a first line approach, and (7) adapt preclinical models to the targeted mechanisms with translational biomarkers to increase their predictive value. © 2020 International Parkinson and Movement Disorder Society.

More Sensitive Identification for Bradykinesia Compared to Tremors in Parkinson's Disease Based on Parkinson's KinetiGraph (PKG)

The effective management and therapies for Parkinson's disease (PD) require appropriate clinical evaluation. The Parkinson's KinetiGraph (PKG) is a wearable sensor system that can monitor the motion characteristics of PD objectively and continuously. This study was aimed to assess the correlations between PKG data and clinical scores of bradykinesia, rigidity, tremor, and fluctuation. It also aims to explore the application value of identifying early motor symptoms. An observational study of 100 PD patients wearing the PKG for ≥ 6 days was performed. It provides a series of data, such as the bradykinesia score (BKS), percent time tremor (PTT), dyskinesia score (DKS), and fluctuation and dyskinesia score (FDS). PKG data and UPDRS scores were analyzed, including UPDRS III total scores, UPDRS III-bradykinesia scores (UPDRS III-B: items 23-26, 31), UPDRS III-rigidity scores (UPDRS III-R: item 22), and scores from the Wearing-off Questionnaire (WOQ-9). This study shows that there was significant correlation between BKS and UPDRS III scores, including UPDRS III total scores, UPDRS III-B, and UPDRS III-R scores (r = 0.479-0.588, p ≤ 0.001), especially in the early-stage group (r = 0.682, p < 0.001). Furthermore, we found that BKS in patients with left-sided onset (33.57 ± 5.14, n = 37) is more serious than in patients with right-sided onset (29.87 ± 6.86, n = 26). Our findings support the feasibility of using the PKG to detect abnormal movements, especially bradykinesia in PD. It is suitable for the early detection, remote monitoring, and timely treatment of PD symptoms.

Introducing the Parkinson's KinetiGraph into Routine Parkinson's Disease Care: A 3-Year Single Centre Experience

In an effort to provide timely clinical input for people with Parkinson's disease (PD) in the face of increasing demand and resource limitation in our UK based service, we introduced remote management in place of clinic appointment, including the use of the Parkinson's KinetiGraph (PKG™), a wrist-worn device that provides a continuous measure of movement. We evaluated our reporting methods and findings, the nature of unmet need we identified, our treatment recommendations and the degree of their implementation in our patients whose feedback guided our service developments. Our evaluation highlighted opportunities and challenges associated with incorporating digital data into care traditionally delivered via in-person contact.

Assessment of Wearing Off in Parkinson's disease using objective measurement

BACKGROUND

Development of "Wearing Off" (WO) of motor and non-motor function in Parkinson's disease (PD) adversely affects quality of life. This suggest that identifying and treating WO is important. However, identification of WO depends on people with PD (PwP) recognising and reporting WO and there is a perception that WO may be significantly underestimated.

OBJECTIVE

We investigate the feasibility of identifying "Wearing Off" using objective measurement and assess the clinical benefit in rectifying it.

METHOD

In this study, 200 PwP were studied for evidence of WO using a continuously worn wearable system. Eighty-five patients (43%) were found to have WO and treatment was changed to mitigate the effects of WO.

RESULTS

Factors, such as duration of disease, high baseline MDS-UPDRS (motor component), high Percent Time in Bradykinesia (PTB), high Levodopa Equivalent Daily Dose (LEDD), frequent Levodopa doses and younger age of onset, are associated with severity of motor complications. Patients with more severe WO experienced worse motor and non-motor symptoms and lower quality of life. Quality of life significantly improved in PwP when WO was treated.

CONCLUSION

The findings reported in this study provide evidence that identifying and treating WO improves outcomes of PwP and that objective measurements may help clinicians to identify and treat WO.

Application of the '5-2-1' screening criteria in advanced Parkinson's disease: interim analysis of DUOGLOBE

Aim: A Delphi expert consensus panel proposed that fulfilling ≥1 of the '5-2-1 criteria' (≥five-times daily oral levodopa use, ≥two daily hours with 'Off' symptoms or ≥one daily hour with troublesome dyskinesia) suggests advanced Parkinson's disease (PD). Patients & methods: DUOdopa/Duopa in Patients with Advanced PD - a GLobal OBservational Study Evaluating Long-Term Effectiveness (DUOGLOBE) - is a single-arm, postmarketing, observational, long-term effectiveness study of levodopa-carbidopa intestinal gel (LCIG) for advanced PD. Results: This 6-month interim analysis (n = 139) affirms that most (98%) enrolled patients fulfill ≥1 of the 5-2-1 criteria. These patients responded favorably to LCIG treatment. Safety was consistent with other LCIG studies. Conclusion: In advanced PD patients, the 5-2-1 criteria generally aligns with clinician assessment. Clinical Trial Registration: NCT02611713 (ClinicalTrials.gov).

Role of microtubule-associated protein 6 glycosylated with Gal-(β-1,3)-GalNAc in Parkinson's disease

Aberrant glycosylation of proteins has major implications for human diseases. To determine whether protein glycosylation contributes to the pathogenesis of Parkinson’s disease (PD), a mouse model of PD was established by injection of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Induction of PD-like features was verified by assessing motor impairment and confirming reductions in biological markers, including dopamine, 5-hydroxytryptamine and tyrosine hydroxylase, as well as the aggregation of α-synuclein. Altered glycosylation was detected using biotinylated agaracus bisporus lectin, which specifically binds exposed Gal-(β-1,3)-GalNAc linked to glycoproteins. Subsequent lectin affinity chromatography coupled with mass spectrometry revealed enhanced glycosylation of microtubule-associated protein 6 (MAP6) in PD mice as compared to healthy controls. In situ dual co-immunofluorescence analysis and immunoblotting confirmed that MAP6 is glycosylated with Gal-(β-1,3)-GalNAc oligosaccharides, which in turn alters the distribution and structure of MAP6 complexes within neurons. This is the first study to described MAP6 as a glycoprotein containing Gal-(β-1,3)-GalNAc oligosaccharides and to show that hyperglycosylation of MAP6 is strongly associated with the pathogenesis of PD. These findings provide potentially valuable information for developing new therapeutic targets for the treatment of PD as well as reliably prognostic biomarkers.

Qualitative Evaluation of the Personal KinetiGraphTM Movement Recording System in a Parkinson's Clinic

Background:

Wearable sensors provide accurate, continuous objective measurements, quantifying the variable motor states of patients with Parkinson’s disease (PD) in real time.

Objectives:

To evaluate the impact of using continuous objective measurement using the Personal KinetiGraph™ (PKG^®) Movement Recording System in the routine clinical care of patients with PD (PwP).

Methods:

Physicians employed the use of the PKG in patients for whom they were seeking objective measurement. Patients wore a PKG data logger for ≥6 days during routine daily living activities. During the survey period of December 2015 through July 2016, physician surveys were completed by four Movement Disorder Specialists for whom measurements from the PKG were available during a subsequent routine clinic visit.

Results:

Of 112 completed physician surveys, 46 (41%) indicated the PKG provided relevant additional information sufficient to consider adjusting their therapeutic management plan; 66 (59%) indicated the PKG provided no further information to support a therapeutic decision differing from that made during a routine clinical evaluation. Upon further review of these 46 surveys, 36 surveys (78%) revealed the information provided by the PKG ultimately resulted in adjusting the patient’s medical management.

Conclusions:

The PKG provided novel additional information beyond that captured during a routine clinic visit sufficient to change the medical management of PwP. Physicians adjusted treatment nearly a third of the time based on data provided by real-time, remote monitoring outside the clinic setting. The use of the PKG may provide for better informed therapeutic decisions, improving the quality of life for PwP.

Management of Advanced Therapies in Parkinson's Disease Patients in Times of Humanitarian Crisis: The COVID-19 Experience

BACKGROUND

Although the COVID-19 pandemic is affecting a relatively small proportion of the global population, its effects have already reached everyone. The pandemic has the potential to differentially disadvantage chronically ill patients, including those with Parkinson's disease (PD). The first health care reaction has been to limit access to clinics and neurology wards to preserve fragile patients with PD from being infected. In some regions, the shortage of medical staff has also forced movement disorders neurologists to provide care for patients with COVID-19.

OBJECTIVE

To share the experience of various movement disorder neurologists operating in different world regions and provide a common approach to patients with PD, with a focus on those already on advanced therapies, which may serve as guidance in the current pandemic and for emergency situations that we may face in the future.

CONCLUSION

Most of us were unprepared to deal with this condition given that in many health care systems, telemedicine has been only marginally available or only limited to email or telephone contacts. In addition, to ensure sufficient access to intensive care unit beds, most elective procedures (including deep brain stimulation or the initiation of infusion therapies) have been postponed. We all hope there will soon be a time when we will return to more regular hospital schedules. However, we should consider this crisis as an opportunity to change our approach and encourage our hospitals and health care systems to facilitate the remote management of chronic neurological patients, including those with advanced PD.

Objective measurement in Parkinson's disease: a descriptive analysis of Parkinson's symptom scores from a large population of patients across the world using the Personal KinetiGraph®

Background

The Personal KinetiGraph® (PKG®) Movement Recording System provides continuous, objective, ambulatory movement data during routine daily activities and provides information on medication compliance, motor fluctuations, immobility, and tremor for patients with Parkinson’s disease (PD). Recent evidence has proposed targets for treatable symptoms. Indications for PKG vary by country and patient selection varies by physician.

Methods

The analyses were based upon 27,834 complete and de-identified PKGs from January 2012 to August 2018 used globally for routine clinical care. Median scores for bradykinesia (BKS) and dyskinesia (DKS) as well as percent time with tremor (PTT) and percent time immobile (PTI) were included as well as proportions of PKGs above published PKG summary score target values (BKS > 25, DKS > 9, PTT > 1%, PTI > 10%). Two sub-analyses included subjects who had 2+ PKG records and scores above proposed BKS and DKS targets, respectively, on their first PKG. Median BKS and DKS scores for subsequent PKGs (1st, 2nd, etc.) were summarized and limited to those with 100+ subsequent PKGs for each data point.

Results

Significant differences between countries were found for all 4 PKG parameter median scores (all p < 0.0001). Overall, 54% of BKS scores were > 25 and ranged from 46 to 61% by country. 10% of all DKS scores were > 9 and ranged from 5 to 15% by country. Sub-analysis for BKS showed global median BKS and DKS scores across subsequent PKGs for subjects who had 2+ PKGs and had BKS > 25 on their first PKG. There were significant changes in BKS from 1st to 2nd-6th PKGs (all p < 0.0001). Sub-analysis for DKS showed global median BKS & DKS scores across subsequent PKGs for subjects who had 2+ PKGs and had DKS > 9 on their first PKG. There were significant changes in DKS from 1st to 2nd and 3rd PKGs (both p < 0.0001).

Conclusions

This analysis shows that in every country evaluated a meaningful proportion of patients have sub-optimal PD motor symptoms and substantial variations exist across countries. Continuous objective measurement (COM) in routine care of PD enables identification and quantification of PD motor symptoms, which can be used to enhance clinical decision making, track symptoms over time and improve PD symptom scores. Thus, clinicians can use these PKG scores during routine clinical management to identify PD symptoms and work to move patients into a target range or a more controlled symptom state.

Prediction of the Levodopa Challenge Test in Parkinson's Disease Using Data from a Wrist-Worn Sensor

The response to levodopa (LR) is important for managing Parkinson’s Disease and is measured with clinical scales prior to (OFF) and after (ON) levodopa. The aim of this study was to ascertain whether an ambulatory wearable device could predict the LR from the response to the first morning dose. The ON and OFF scores were sorted into six categories of severity so that separating Parkinson’s Kinetigraph (PKG) features corresponding to the ON and OFF scores became a multi-class classification problem according to whether they fell below or above the threshold for each class. Candidate features were extracted from the PKG data and matched to the class labels. Several linear and non-linear candidate statistical models were examined and compared to classify the six categories of severity. The resulting model predicted a clinically significant LR with an area under the receiver operator curve of 0.92. This study shows that ambulatory data could be used to identify a clinically significant response to levodopa. This study has also identified practical steps that would enhance the reliability of this test in future studies.

Non-motor correlates of wrist-worn wearable sensor use in Parkinson's disease: an exploratory analysis

Wearable sensors are becoming increasingly more available in Parkinson’s disease and are used to measure motor function. Whether non-motor symptoms (NMS) can also be measured with these wearable sensors remains unclear. We therefore performed a retrospective, exploratory, analysis of 108 patients with a diagnosis of idiopathic Parkinson’s disease enroled in the Non-motor Longitudinal International Study (UKCRN No. 10084) at King’s College Hospital, London, to determine the association between the range and nature of NMS and an accelerometer-based outcome measure of bradykinesia (BKS) and dyskinesia (DKS). NMS were assessed by the validated NMS Scale, and included, e.g., cognition, mood and sleep, and gastrointestinal, urinary and sexual problems. Multiple linear regression modelling was used to identify NMS associated with BKS and DKS. We found that BKS was associated with domains 6 (gastrointestinal tract; p = 0.006) and 8 (sexual function; p = 0.003) of the NMS scale. DKS was associated with domains 3 (mood/cognition; p = 0.016), 4 (perceptual problems; p = 0.025), 6 (gastrointestinal tract; p = 0.029) and 9 (miscellaneous, p = 0.003). In the separate domains, constipation was significantly associated with BKS. Delusions, dysphagia, hyposmia, weight change and hyperhidrosis were identified as significantly associated with DKS. None of the NMSS domains were associated with disease duration (p ≥ 0.08). In conclusion, measures of BKS and DKS were mainly associated with gastrointestinal problems, independent of disease duration, showing the potential for wearable devices to pick up on these symptoms. These exploratory results deserve further exploration, and more research on this topic in the form of comprehensive large-scale studies is needed.

[Wearables in the treatment of neurological diseases-where do we stand today?]

Fitness and lifestyle trackers raise the awareness for wearable sensors in medical applications for clinical trials and healthcare. Various functional impairments of patients with neurological diseases are an ideal target to generate wearable-derived and patient-centered parameters that have the potential to support prevention, prediction, diagnostic procedures and therapy monitoring during the clinical work-up; however, substantial differences between clinical grade wearables and fitness trackers have to be acknowledged. For the application in clinical trials or individualized patient care distinct technical and clinical validation trials have to be conducted. The different test environments under laboratory conditions during standardized tests or under unsupervised home monitoring conditions have to be included in the algorithmic processing of sensor raw data in order to enable a clinical decision support under real-life conditions. This article presents the general understanding of the technical application for the most relevant functional impairments in neurology. While wearables used for sleep assessment have already reached a high level of technological readiness due to the defined test environment (bed, sleep), other wearable applications, e.g. for gait and mobility during home monitoring require further research in order to transfer the technical capabilities into real-life patient care.

"You have to know why you're doing this": a mixed methods study of the benefits and burdens of self-tracking in Parkinson's disease

BACKGROUND

This study explores opinions and experiences of people with Parkinson's disease (PwP) in Sweden of using self-tracking. Parkinson's disease (PD) is a neurodegenerative condition entailing varied and changing symptoms and side effects that can be a challenge to manage optimally. Patients' self-tracking has demonstrated potential in other diseases, but we know little about PD self-tracking. The aim of this study was therefore to explore the opinions and experiences of PwP in Sweden of using self-tracking for PD.

METHOD

A mixed methods approach was used, combining qualitative data from seven interviews with quantitative data from a survey to formulate a model for self-tracking in PD. In total 280 PwP responded to the survey, 64% (n = 180) of which had experience from self-tracking.

RESULT

We propose a model for self-tracking in PD which share distinctive characteristics with the Plan-Do-Study-Act (PDSA) cycle for healthcare improvement. PwP think that tracking takes a lot of work and the right individual balance between burdens and benefits needs to be found. Some strategies have here been identified; to focus on positive aspects rather than negative, to find better solutions for their selfcare, and to increase the benefits through improved tools and increased use of self-tracking results in the dialogue with healthcare.

CONCLUSION

The main identified benefits are that self-tracking gives PwP a deeper understanding of their own specific manifestations of PD and contributes to a more effective decision making regarding their own selfcare. The process of self-tracking also enables PwP to be more active in communicating with healthcare. Tracking takes a lot of work and there is a need to find the right balance between burdens and benefits.

A novel single-sensor-based method for the detection of gait-cycle breakdown and freezing of gait in Parkinson's disease

Objective measurement of walking speed and gait deficits are an important clinical tool in chronic illness management. We previously reported in Parkinson's disease that different types of gait tests can now be implemented and administered in the clinic or at home using Ambulosono smartphone-sensor technology, whereby movement sensing protocols can be standardized under voice instruction. However, a common challenge that remains for such wearable sensor systems is how meaningful data can be extracted from seemingly "noisy" raw sensor data, and do so with a high level of accuracy and efficiency. Here, we describe a novel pattern recognition algorithm for the automated detection of gait-cycle breakdown and freezing episodes. Ambulosono-gait-cycle-breakdown-and-freezing-detection (Free-D) integrates a nonlinear m-dimensional phase-space data extraction method with machine learning and Monte Carlo analysis for model building and pattern generalization. We first trained Free-D using a small number of data samples obtained from thirty participants during freezing of gait tests. We then tested the accuracy of Free-D via Monte Carlo cross-validation. We found Free-D to be remarkably effective at detecting gait-cycle breakdown, with mode error rates of 0% and mean error rates < 5%. We also demonstrate the utility of Free-D by applying it to continuous holdout traces not used for either training or testing, and found it was able to identify gait-cycle breakdown and freezing events of varying duration. These results suggest that advanced artificial intelligence and automation tools can be developed to enhance the quality, efficiency, and the expansion of wearable sensor data processing capabilities to meet market and industry demand.