Evaluation of the Parkinson’s KinetiGraph in monitoring and managing Parkinson’s disease

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.

Home-based monitoring of persons with advanced Parkinson's disease using smartwatch-smartphone technology

Movement deterioration is the hallmark of Parkinson's disease (PD), characterized by levodopa-induced motor-fluctuations (i.e., symptoms' variability related to the medication cycle) in advanced stages. However, motor symptoms are typically too sporadically and/or subjectively assessed, ultimately preventing the effective monitoring of their progression, and thus leading to suboptimal treatment/therapeutic choices. Smartwatches (SW) enable a quantitative-oriented approach to motor-symptoms evaluation, namely home-based monitoring (HBM) using an embedded inertial measurement unit. Studies validated such approach against in-clinic evaluations. In this work, we aimed at delineating personalized motor-fluctuations' profiles, thus capturing individual differences. 21 advanced PD patients with motor fluctuations were monitored for 2 weeks using a SW and a smartphone-dedicated app (Intel Pharma Analytics Platform). The SW continuously collected passive data (tremor, dyskinesia, level of activity using dedicated algorithms) and active data, i.e., time-up-and-go, finger tapping, hand tremor and hand rotation carried out daily, once in OFF and once in ON levodopa periods. We observed overall high compliance with the protocol. Furthermore, we observed striking differences among the individual patterns of symptoms' levodopa-related variations across the HBM, allowing to divide our participants among four data-driven, motor-fluctuations' profiles. This highlights the potential of HBM using SW technology for revolutionizing clinical practices.

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.

Predicting Motor Outcome and Quality of Life After Subthalamic Deep Brain Stimulation for Parkinson's Disease: The Role of Standard Screening Measures and Wearable-Data

BACKGROUND

Standardized screening for subthalamic deep brain stimulation (STN DBS) in Parkinson's disease (PD) patients is crucial to determine eligibility, but its utility to predict postoperative outcomes in eligible patients is inconclusive. It is unknown whether wearable data can contribute to this aim.

OBJECTIVE

To evaluate the utility of universal components incorporated in the DBS screening, complemented by a wearable sensor, to predict motor outcomes and Quality of life (QoL) one year after STN DBS surgery.

METHODS

Consecutive patients were included in the OPTIMIST cohort study from two DBS centers. Standardized assessments included a preoperative Levodopa Challenge Test (LCT), and questionnaires on QoL and non-motor symptoms including cognition, psychiatric symptoms, impulsiveness, autonomic symptoms, and sleeping problems. Moreover, an ambulatory wearable sensor (Parkinson Kinetigraph (PKG)) was used. Postoperative assessments were similar and also included a Stimulation Challenge Test to determine DBS effects on motor function.

RESULTS

Eighty-three patients were included (median (interquartile range) age 63 (56-68) years, 36% female). Med-OFF (Stim-OFF) motor severity deteriorated indicating disease progression, but patients significantly improved in terms of Med-ON (Stim-ON) motor function, motor fluctuations, QoL, and most non-motor domains. Motor outcomes were not predicted by preoperative tests, including covariates of either LCT or PKG. Postoperative QoL was predicted by better preoperative QoL, lower age, and more preoperative impulsiveness scores in multivariate models.

CONCLUSION

Data from the DBS screening including wearable data do not predict postoperative motor outcome at one year. Post-DBS QoL appears primarily driven by non-motor symptoms, rather than by motor improvement.

Deep Clinical Phenotyping of Parkinson's Disease: Towards a New Era of Research and Clinical Care

Despite recent advances in technology, clinical phenotyping of Parkinson's disease (PD) has remained relatively limited as current assessments are mainly based on empirical observation and subjective categorical judgment at the clinic. A lack of comprehensive, objective, and quantifiable clinical phenotyping data has hindered our capacity to diagnose, assess patients' conditions, discover pathogenesis, identify preclinical stages and clinical subtypes, and evaluate new therapies. Therefore, deep clinical phenotyping of PD patients is a necessary step towards understanding PD pathology and improving clinical care. In this review, we present a growing community consensus and perspective on how to clinically phenotype this disease, that is, to phenotype the entire course of disease progression by integrating capacity, performance, and perception approaches with state-of-the-art technology. We also explore the most studied aspects of PD deep clinical phenotypes, namely, bradykinesia, tremor, dyskinesia and motor fluctuation, gait impairment, speech impairment, and non-motor phenotypes.

Toward Improved Treatment and Empowerment of Individuals With Parkinson Disease: Design and Evaluation of an Internet of Things System

Background

Parkinson disease (PD) is a chronic degenerative disorder that causes progressive neurological deterioration with profound effects on the affected individual’s quality of life. Therefore, there is an urgent need to improve patient empowerment and clinical decision support in PD care. Home-based disease monitoring is an emerging information technology with the potential to transform the care of patients with chronic illnesses. Its acceptance and role in PD care need to be elucidated both among patients and caregivers.

Objective

Our main objective was to develop a novel home-based monitoring system (named EMPARK) with patient and clinician interface to improve patient empowerment and clinical care in PD.

Methods

We used elements of design science research and user-centered design for requirement elicitation and subsequent information and communications technology (ICT) development. Functionalities of the interfaces were the subject of user-centric multistep evaluation complemented by semantic analysis of the recorded end-user reactions. The ICT structure of EMPARK was evaluated using the ICT for patient empowerment model.

Results

Software and hardware system architecture for the collection and calculation of relevant parameters of disease management via home monitoring were established. Here, we describe the patient interface and the functional characteristics and evaluation of a novel clinician interface. In accordance with our previous findings with regard to the patient interface, our current results indicate an overall high utility and user acceptance of the clinician interface. Special characteristics of EMPARK in key areas of interest emerged from end-user evaluations, with clear potential for future system development and deployment in daily clinical practice. Evaluation through the principles of ICT for patient empowerment model, along with prior findings from patient interface evaluation, suggests that EMPARK has the potential to empower patients with PD.

Conclusions

The EMPARK system is a novel home monitoring system for providing patients with PD and the care team with feedback on longitudinal disease activities. User-centric development and evaluation of the system indicated high user acceptance and usability. The EMPARK infrastructure would empower patients and could be used for future applications in daily care and research.

Fitts Law-Based Performance Metrics to Quantify Tremor in Individuals with Essential Tremor

Current methods of evaluating essential tremor (ET) either rely on subjective ratings or use limited tremor metrics (i.e., severity/amplitude and frequency). In this study, we explored performance metrics from Fitts law tasks that replicate and expand existing tremor metrics, to enable low-cost, home-based tremor quantification and analyze the cursor movements of individuals using a 3D mouse while performing a collection of drawing tasks. We analyzed the 3D mouse cursor movements of 11 patients with ET and three controls, on three computer-based tasksa spiral navigation (SPN) task, a rectangular track navigation (RTN) task, and multi-directional tapping/clicking (MDT)with several performance metrics (i.e., outside area (OA), throughput (TP in Fitts law), path efficiency (PE), and completion time (CT)). Using an accelerometer and scores from the Essential Tremor Rating Assessment Scale (TETRAS), we correlated the proposed performance metrics with the baseline tremor metrics and found that the OA of the SPN and RTN tasks were strongly correlated with baseline tremor severity (R²=0.57 and R²=0.83). We also found that the TP in the MDT tasks were strongly correlated with tremor frequency (R²=0.70). In addition, as the OA of the SPN and RTN tasks was correlated with tremor severity and frequency, it may represent an independent metric that increases the dimensionality of the characterization of an individuals tremor. Thus, this pilot study of the analysis of those with ET-associated tremor performing Fitts law tasks demonstrates the feasibility of introducing a new tremor metric that can be expanded for repeatable multi-dimensional data analyses.

Comparison of the Parkinson's KinetiGraph to off/on levodopa response testing: Single center experience

BACKGROUND AND OBJECTIVE

Levodopa off/on testing is frequently performed to assess medication response in patients with Parkinson's disease (PD) as an aid in determining best medical management or potential surgical candidacy. The Parkinson's Kinetigraph (PKG) is a wearable device which generates tremor, bradykinesia (BKS) and dyskinesia (DKS) scores representing motor symptoms over a six-day period. In this study, we compared off/on testing with PKG motor scores.

METHODS

Patients were enrolled as part of an observational study: Assessing the Longitudinal Signs in PD, a three-year study evaluating clinical and biomarker evolution in patients with PD taking levodopa. Patients underwent off/on testing at baseline and 6-month visits. A greater than 30% improvement between off and on MDS-Unified Parkinson's Disease Rating Scale scores was considered a robust response. After each visit, patients wore the PKG for 6 days. A bradykinesia score (BKS) greater than 26 and dyskinesia score (DKS) greater than 9 were considered poorly controlled bradykinesia and dyskinesia, respectively.

RESULTS

The median BKS at the baseline and 6-month visits were 27.15 and 27.55, respectively, despite a robust median off/on improvement at both visits. In addition, 10/18 (66%) and 7/13 (53.8%) patients with robust off/on improvement at the baseline and 6-month visits, respectively, demonstrated a BKS > 26 or DKS > 9.

CONCLUSION

A robust off/on response during a clinic visit does not necessarily reflect adequately controlled motor symptoms. The PKG, by virtue of its continuous recording of motor movements, may provide additional clinically relevant data on motor symptoms which may be useful for prospective observational studies.

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.

Comparing subjective and objective response to medications in Parkinson's disease patients using the Personal KinetiGraph™

BACKGROUND

Management of motor symptoms in Parkinson's Disease(PD) relies on subjective information provided by patients, the quality of which can be affected by many factors.

RATIONALE

Objective data collected during daily life could complement this information and improve management of motor symptoms.

OBJECTIVES

To assess the usefulness of the Personal KinetiGraph (PKG) in characterizing the intensity and timing of motor symptoms in PD patients.

METHODS

Retrospective study of all PD patients followed at a tertiary academic movement disorders center assessed by PKG between December 1, 2016 and October 30, 2018. PKG was worn for 7 days prior to the clinical visit. We compared the information obtained from the interview and the clinical visit, and assessed the impact of the PKG on treatment decision making.

RESULTS

170 PKG results were reviewed. PKG complemented patient input in 82.9%(141/170) and led to medication changes in 71%(100/141) of the complemented inputs. PKG contributed the least to correcting or complementing patients' input when patients self-reported as undertreated (22%) and the most when patient were unable to answer all questions regarding motor response to individual doses (100%) (Fisher, p < 0.0001). The majority of patient undergoing 3 or 4 PKG encounters did not reach a controlled state as defined by PKG until the 3rd or 4th encounter, suggesting that repeated use of the PKG might be needed to help optimize motor control as therapy changes done after one encounter might not be enough.

CONCLUSIONS

PKG might be useful in supplementing patient-provided information for accurate assessment and treatment plan.

Precompetitive Consensus Building to Facilitate the Use of Digital Health Technologies to Support Parkinson Disease Drug Development through Regulatory Science

Innovative tools are urgently needed to accelerate the evaluation and subsequent approval of novel treatments that may slow, halt, or reverse the relentless progression of Parkinson disease (PD). Therapies that intervene early in the disease continuum are a priority for the many candidates in the drug development pipeline. There is a paucity of sensitive and objective, yet clinically interpretable, measures that can capture meaningful aspects of the disease. This poses a major challenge for the development of new therapies and is compounded by the considerable heterogeneity in clinical manifestations across patients and the fluctuating nature of many signs and symptoms of PD. Digital health technologies (DHT), such as smartphone applications, wearable sensors, and digital diaries, have the potential to address many of these gaps by enabling the objective, remote, and frequent measurement of PD signs and symptoms in natural living environments. The current climate of the COVID-19 pandemic creates a heightened sense of urgency for effective implementation of such strategies. In order for these technologies to be adopted in drug development studies, a regulatory-aligned consensus on best practices in implementing appropriate technologies, including the collection, processing, and interpretation of digital sensor data, is required. A growing number of collaborative initiatives are being launched to identify effective ways to advance the use of DHT in PD clinical trials. The Critical Path for Parkinson's Consortium of the Critical Path Institute is highlighted as a case example where stakeholders collectively engaged regulatory agencies on the effective use of DHT in PD clinical trials. Global regulatory agencies, including the US Food and Drug Administration and the European Medicines Agency, are encouraging the efficiencies of data-driven engagements through multistakeholder consortia. To this end, we review how the advancement of DHT can be most effectively achieved by aligning knowledge, expertise, and data sharing in ways that maximize efficiencies.

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.

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.

Wearable technology to assess bradykinesia and immobility in patients with severe depression undergoing electroconvulsive therapy: A pilot study

The psychomotor retardation that may be seen in major depression represents an interesting parallel to bradykinesia, a core feature of Parkinson's disease. Psychomotor retardation has been correlated with the severity of depression and is a predictor of response to electroconvulsive therapy (ECT). Psychomotor retardation has typically been assessed by subjective clinical judgement including clinical rating scales. Gross activity levels have also been measured with actigraphy previously. The Parkinson's KinetiGraph (PKG) was developed to assess bradykinesia, dyskinesia and tremor in Parkinson's disease and allows for an objective assessment of motor symptoms over time. It has not been used previously to assess motor symptoms in depression. The aim of the current pilot study was to use the PKG to objectively measure both bradykinesia and immobility in depressed inpatients undergoing ECT before, during and at the end of therapy and review correlations with depressive symptomatology and treatment response. The majority of patients (9/12) had PKG defined bradykinesia at baseline and 7/9 of these improved with ECT. All patients with bradykinesia who remitted clinically demonstrated improvements in bradykinesia scores. PKG defined immobility was present at baseline in 11/12 total patients and improved in the majority of these patients (9/11) post ECT. Correlations between clinically assessed melancholia and PKG measures were significant (r = 0.701, p 0.011 at baseline to r_s = 0.655, p 0.021 at end). A strong association between bradykinesia and immobility scores and depression severity was not seen. The PKG is a potentially useful wearable technology to objectively assess motor symptoms in depression.

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.

"Does the Response to Morning Medication Predict the ADL-Level of the Day in Parkinson's Disease?"

Background

Individuals with Parkinson's Disease (PD) have bradykinesia during mobility tasks in the morning before intake of dopaminergic treatment and have difficulties managing Activities of Daily Living (ADLs). Early morning off (EMO) refers to off-states in the morning where the severity of bradykinesia is increased and causes a decrease in mobility related to wearing off of effects of medication. Measurements from devices capable of continuously recording motor symptoms may provide insight into the patient's response to medication and possible impact on ADLs.

Objectives

To test whether poor or slow response to medication in the morning predicts the overall ADL-level and to assess the association between change in bradykinesia score (BKS) and the risk of having disabilities within three selected ADL-items.

Methods

In this cross-sectional study, the sample consists of 34 patients with light to moderate PD. Data collection encompasses measurements from the Parkinson KinetiGraph, and the ADL-limitations are assessed by the Movement Disorder Society Unified Parkinson Disease Rating Scale (MDS-UPDRS) Part II.

Results

The association between UPDRS- II and BKS from the algorithm was -0.082 (p < 0.01), 95% CL:-0.113; -0.042). The individuals experienced disabilities in performing "Speech" (p=0.004) and "Doing hobbies" (p=0.038) when being slow or poor responders to dopaminergic therapy. The PD patients' L-dopa equivalent dose seems to be a strong predictor of the ADL-level in the morning.

Conclusion

Slow response to the medication dosages in the morning is correlated with disabilities in the overall ADL-level in PD. The combination of PD-drugs and precise, timely dosages must be considered in the improvement of the ADL-level in PD patients.

New Sensor and Wearable Technologies to Aid in the Diagnosis and Treatment Monitoring of Parkinson's Disease

Parkinson's disease (PD) is a degenerative disorder of the brain characterized by the impairment of the nigrostriatal system. This impairment leads to specific motor manifestations (i.e., bradykinesia, tremor, and rigidity) that are assessed through clinical examination, scales, and patient-reported outcomes. New sensor-based and wearable technologies are progressively revolutionizing PD care by objectively measuring these manifestations and improving PD diagnosis and treatment monitoring. However, their use is still limited in clinical practice, perhaps because of the absence of external validation and standards for their continuous use at home. In the near future, these systems will progressively complement traditional tools and revolutionize the way we diagnose and monitor patients with PD.

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.

The Use of Data from the Parkinson's KinetiGraph to Identify Potential Candidates for Device Assisted Therapies

Device-assisted therapies (DAT) benefit people with Parkinsons Disease (PwP) but many referrals for DAT are unsuitable or too late, and a screening tool to aid in identifying candidates would be helpful. This study aimed to produce such a screening tool by building a classifier that models specialist identification of suitable DAT candidates. To our knowledge, this is the first objective decision tool for managing DAT referral. Subjects were randomly assigned to either a construction set (n = 112, to train, develop, cross validate, and then evaluate the classifier’s performance) or to a test set (n = 60 to test the fully specified classifier), resulting in a sensitivity and specificity of 89% and 86.6%, respectively. The classifier’s performance was then assessed in PwP who underwent deep brain stimulation (n = 31), were managed in a non-specialist clinic (n = 81) or in PwP in the first five years from diagnosis (n = 22). The classifier identified 87%, 92%, and 100% of the candidates referred for DAT in each of the above clinical settings, respectively. Furthermore, the classifier score changed appropriately when therapeutic intervention resolved troublesome fluctuations or dyskinesia that would otherwise have required DAT. This study suggests that information from objective measurement could improve timely referral for DAT.

CDNF Protein Therapy in Parkinson's Disease

Neurotrophic factors (NTF) are a subgroup of growth factors that promote survival and differentiation of neurons. Due to their neuroprotective and neurorestorative properties, their therapeutic potential has been tested in various neurodegenerative diseases. Bioavailability of NTFs in the target tissue remains a major challenge for NTF-based therapies. Various intracerebral delivery approaches, both protein and gene transfer-based, have been tested with varying outcomes. Three growth factors, glial cell-line derived neurotrophic factor (GDNF), neurturin (NRTN) and platelet-derived growth factor (PDGF-BB) have been tested in clinical trials in Parkinson’s disease (PD) during the past 20 years. A new protein can now be added to this list, as cerebral dopamine neurotrophic factor (CDNF) has recently entered clinical trials. Despite their misleading names, CDNF, together with its closest relative mesencephalic astrocyte-derived neurotrophic factor (MANF), form a novel family of unconventional NTF that are both structurally and mechanistically distinct from other growth factors. CDNF and MANF are localized mainly to the lumen of endoplasmic reticulum (ER) and their primary function appears to be modulation of the unfolded protein response (UPR) pathway. Prolonged ER stress, via the UPR signaling pathways, contributes to the pathogenesis in a number of chronic degenerative diseases, and is an important target for therapeutic modulation. Intraputamenally administered recombinant human CDNF has shown robust neurorestorative effects in a number of small and large animal models of PD, and had a good safety profile in preclinical toxicology studies. Intermittent monthly bilateral intraputamenal infusions of CDNF are currently being tested in a randomized placebo-controlled phase I–II clinical study in moderately advanced PD patients. Here, we review the history of growth factor-based clinical trials in PD, and discuss how CDNF differs from the previously tested growth factors.

Identification of Motor Symptoms Related to Parkinson Disease Using Motion-Tracking Sensors at Home (KÄVELI): Protocol for an Observational Case-Control Study

Background

Clinical characterization of motion in patients with Parkinson disease (PD) is challenging: symptom progression, suitability of medication, and level of independence in the home environment can vary across time and patients. Appointments at the neurological outpatient clinic provide a limited understanding of the overall situation. In order to follow up these variations, longer-term measurements performed outside of the clinic setting could help optimize and personalize therapies. Several wearable sensors have been used to estimate the severity of symptoms in PD; however, longitudinal recordings, even for a short duration of a few days, are rare. Home recordings have the potential benefit of providing a more thorough and objective follow-up of the disease while providing more information about the possible need to change medications or consider invasive treatments.

Objective

The primary objective of this study is to collect a dataset for developing methods to detect PD-related symptoms that are visible in walking patterns at home. The movement data are collected continuously and remotely at home during the normal lives of patients with PD as well as controls. The secondary objective is to use the dataset to study whether the registered medication intakes can be identified from the collected movement data by looking for and analyzing short-term changes in walking patterns.

Methods

This paper described the protocol for an observational case-control study that measures activity using three different devices: (1) a smartphone with a built-in accelerometer, gyroscope, and phone orientation sensor, (2) a Movesense smart sensor to measure movement data from the wrist, and (3) a Forciot smart insole to measure the forces applied on the feet. The measurements are first collected during the appointment at the clinic conducted by a trained clinical physiotherapist. Subsequently, the subjects wear the smartphone at home for 3 consecutive days. Wrist and insole sensors are not used in the home recordings.

Results

Data collection began in March 2018. Subject recruitment and data collection will continue in spring 2019. The intended sample size was 150 subjects. In 2018, we collected a sample of 103 subjects, 66 of whom were diagnosed with PD.

Conclusions

This study aims to produce an extensive movement-sensor dataset recorded from patients with PD in various phases of the disease as well as from a group of control subjects for effective and impactful comparison studies. The study also aims to develop data analysis methods to monitor PD symptoms and the effects of medication intake during normal life and outside of the clinic setting. Further applications of these methods may include using them as tools for health care professionals to monitor PD remotely and applying them to other movement disorders.

Trial Registration

ClinicalTrials.gov NCT03366558; https://clinicaltrials.gov/ct2/show/NCT03366558 

International Registered Report Identifier (IRRID)

DERR1-10.2196/12808

Objective measurement in routine care of people with Parkinson's disease improves outcomes

It is common in medicine to titrate therapy according to target ranges of objectively measured parameters. Objective measurement of motor function is available for Parkinson's Disease (PD), making it possible to optimise therapy and clinical outcomes. In this study, an accelerometry based measurement and predefined target ranges were used to assess motor function in a Northern Tasmania PD cohort managed by a Movement Disorder clinic. Approximately 40% (n = 103) of the total PD population participated in this study and motor scores were within target in 22%. In the 78% above target, changes in oral therapy were recommended in 74%, Advanced Therapy in 12% and treatment was contraindicated in 9%. Following changes in oral therapy, there was a further objective measurement and clinical consultation to establish whether scores had reached target range: if so subjects left the study, otherwise further changes of therapy were recommended (unless contraindications were present). Seventy-seven cases completed the study, with 48% achieving target (including 22% at outset), Advanced Therapy recommended in 19% and contraindications preventing any change in therapy in 17%. In the 43% of cases in whom oral therapy was changed, total UPDRS improved significantly (effect size = 8) as did the PDQ39 in cases reaching target. NMS Quest and MOCA scores also improved significantly. This study shows that many people in a representative cohort of PD would benefit from objective assessment and treatment of their PD features against a target.