Management of Parkinson's Disease 20 Years from Now: Towards Digital Health Pathways

Building digital patient pathways for the management and treatment of multiple sclerosis

Recent advances in the field of artificial intelligence (AI) could yield new insights into the potential causes of multiple sclerosis (MS) and factors influencing its course as the use of AI opens new possibilities regarding the interpretation and use of big data from not only a cross-sectional, but also a longitudinal perspective. For each patient with MS, there is a vast amount of multimodal data being accumulated over time. But for the application of AI and related technologies, these data need to be available in a machine-readable format and need to be collected in a standardized and structured manner. Through the use of mobile electronic devices and the internet it has also become possible to provide healthcare services from remote and collect information on a patient's state of health outside of regular check-ups on site. Against this background, we argue that the concept of pathways in healthcare now could be applied to structure the collection of information across multiple devices and stakeholders in the virtual sphere, enabling us to exploit the full potential of AI technology by e.g., building digital twins. By going digital and using pathways, we can virtually link patients and their caregivers. Stakeholders then could rely on digital pathways for evidence-based guidance in the sequence of procedures and selection of therapy options based on advanced analytics supported by AI as well as for communication and education purposes. As far as we aware of, however, pathway modelling with respect to MS management and treatment has not been thoroughly investigated yet and still needs to be discussed. In this paper, we thus present our ideas for a modular-integrative framework for the development of digital patient pathways for MS treatment.

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

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

Personalized Integrated Care Promoting Quality of Life for Older People: Protocol for a Multicenter Randomized Controlled Trial

BACKGROUND

Alzheimer disease (AD) and Parkinson disease (PD) are the 2 most common neurodegenerative diseases affecting millions of people worldwide. The Personalized Integrated Care Promoting Quality of Life for Older People (PC4L) project proposes an integrated, scalable, and interactive care ecosystem that can be easily adapted to the needs of several neurodegenerative and chronic diseases, care institutions, and end user requirements.

OBJECTIVE

The study protocol developed within the framework of the PC4L project aims to iteratively test the integrated platform and its modules, and focuses primarily on assessing the impact of the proposed solution (ie, the PC4L platform) on patients' quality of life, as well as its usability and feasibility on a large-scale sample size in 3 different scenarios (home, neurorehabilitation, and day care centers).

METHODS

A prospective multicenter clinical study is conducted in 5 European countries (Germany, Italy, Portugal, Romania, and Spain) at 6 different pilot centers, for 3 months, in patients with PD, Parkinsonism, AD, and other dementias (ODs). Patients were randomized in a ratio of 1:1 to the intervention group (use of the PC4L system) or the control group (no intervention). The PC4L system consists mainly of a wristband for monitoring parameters such as steps and levels of physical activity, and the PC4L app, which includes different engaging functionalities. Both groups are assessed through baseline and end-of-study clinical evaluations, including assessment of quality of life through the EQ-5D-3L scale.

RESULTS

The study protocol is part of a project approved and funded by the European Commission Horizon 2020 (grant agreement number 875221). The ethics committees of all involved centers reviewed and approved the study protocol. The study began with the recruitment phase in September 2022, and enrollment ended in February 2023. Recruitment is now closed (April 2023). The results of this study are expected to be published in summer 2023. A total of 558 patients, 279 per study group, were recruited. The results will allow to clarify the impact of PC4L on quality of life, will assess the empowerment of patients and the medical resources use, as well as the usability of the final version of the PC4L system. It will also provide information on the support of the system as a tool to facilitate the decision-making process.

CONCLUSIONS

The PC4L project intends to test a technology-based, integrated, scalable, and interactive care platform on patients with neurodegenerative diseases and proposes a good coordinated care model between all involved actors. Future developments of the PC4L solution may involve caregivers and socio-health professionals in the decision-making process in order to facilitate efficient communication between all stakeholders and ensure reliable and protected access to data within Europe.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05538455; https://clinicaltrials.gov/study/NCT05538455.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/47916.

Predictive Models for Health Deterioration: Understanding Disease Pathways for Personalized Medicine

Artificial intelligence (AI) and machine learning (ML) methods are currently widely employed in medicine and healthcare. A PubMed search returns more than 100,000 articles on these topics published between 2018 and 2022 alone. Notwithstanding several recent reviews in various subfields of AI and ML in medicine, we have yet to see a comprehensive review around the methods' use in longitudinal analysis and prediction of an individual patient's health status within a personalized disease pathway. This review seeks to fill that gap. After an overview of the AI and ML methods employed in this field and of specific medical applications of models of this type, the review discusses the strengths and limitations of current studies and looks ahead to future strands of research in this field. We aim to enable interested readers to gain a detailed impression of the research currently available and accordingly plan future work around predictive models for deterioration in health status.

The definition of precision medicine in neurodegenerative disorders and the one disease-many diseases tension

Precision medicine is a patient-centered approach that aims to translate new knowledge to optimize the type and timing of interventions for the greatest benefit to individual patients. There is considerable interest in applying this approach to treatments designed to slow or halt the progression of neurodegenerative diseases. Indeed, effective disease-modifying treatment (DMT) remains the greatest unmet therapeutic need in this field. In contrast to the enormous progress in oncology, precision medicine in the field of neurodegeneration faces multiple challenges. These are related to major limitations in our understanding of many aspects of the diseases. A critical barrier to advances in this field is the question of whether the common sporadic neurodegenerative diseases (of the elderly) are single uniform disorders (particularly related to their pathogenesis) or whether they represent a collection of related but still very distinct disease states. In this chapter, we briefly touch on lessons from other fields of medicine that might be applied to the development of precision medicine for DMT in neurodegenerative diseases. We discuss why DMT trials may have failed to date, and particularly the importance of appreciating the multifaceted nature of disease heterogeneity and how this has and will impact on these efforts. We conclude with comments on how we can move from this complex disease heterogeneity to the successful application of precision medicine principles in DMT for neurodegenerative diseases.

Need for personalized monitoring of Parkinson's disease: the perspectives of patients and specialized healthcare providers

Background

Digital tools such as wearable sensors may help to monitor Parkinson's disease (PD) in daily life. To optimally achieve the expected benefits, such as personized care and improved self-management, it is essential to understand the perspective of both patients and the healthcare providers.

Objectives

We identified the motivations for and barriers against monitoring PD symptoms among PD patients and healthcare providers. We also investigated which aspects of PD were considered most important to monitor in daily life, and which benefits and limitations of wearable sensors were expected.

Methods

Online questionnaires were completed by 434 PD patients and 166 healthcare providers who were specialized in PD care (86 physiotherapists, 55 nurses, and 25 neurologists). To gain further understanding in the main findings, we subsequently conducted homogeneous focus groups with patients (n = 14), physiotherapists (n = 5), and nurses (n = 6), as well as individual interviews with neurologists (n = 5).

Results

One third of the patients had monitored their PD symptoms in the past year, most commonly using a paper diary. Key motivations were: (1) discuss findings with healthcare providers, (2) obtain insight in the effect of medication and other treatments, and (3) follow the progression of the disease. Key barriers were: (1) not wanting to focus too much on having PD, (2) symptoms being relatively stable, and (3) lacking an easy-to-use tool. Prioritized symptoms of interest differed between patients and healthcare providers; patients gave a higher priority to fatigue, problems with fine motor movements and tremor, whereas professionals more frequently prioritized balance, freezing and hallucinations. Although both patients and healthcare providers were generally positive about the potential of wearable sensors for monitoring PD symptoms, the expected benefits and limitations varied considerably between groups and within the patient group.

Conclusion

This study provides detailed information about the perspectives of patients, physiotherapists, nurses and neurologists on the merits of monitoring PD in daily life. The identified priorities differed considerably between patients and professionals, and this information is critical when defining the development and research agenda for the coming years. We also noted considerable differences in priorities between individual patients, highlighting the need for personalized disease monitoring.

Correlation of biomarker cortisol with fatigue and quality of life among men and women with idiopathic Parkinson’s disease

Introduction and Aim: Fatigue is the prodromal symptom occurring as the earliest symptom even before motor symptoms. It has been unidentified, which also proves to be an untouched symptom for intervention. Little has been understood how men and women feel fatigued. The objective of this study is to find the correlation between fatigue and quality of life among men and women with idiopathic Parkinson’s disease (PD).  Materials and Methods: Recommended scale for fatigue as fatigue severity score and a biomarker salivary cortisol was correlated against the quality-of-life questionnaire as PDQ-39 among 25 PD male and female patients. Results: Females are found to show significantly higher values compared to males in PDQ and salivary cortisol. F values are significant for PDQ and salivary cortisol only (p < 0.01) when compared to the H/Y scale (‘r’ = 0.420). Conclusion: Females reported more fatigue and poor quality of life. Salivary cortisol can be a useful biomarker to measure and infer the level of fatigue which had been only feeling reported by the patients until now.

The Challenges Toward Real-world Implementation of Digital Health Design Approaches: Narrative Review

BACKGROUND

Digital health represents an important strategy in the future of health care delivery. Over the past decade, mobile health has accelerated the agency of health care users. Despite prevailing excitement about the potential of digital health, questions remain on efficacy, uptake, usability, and patient outcome. This challenge is confounded by 2 industries, digital and health, which have vastly different approaches to research, design, testing, and implementation. In this regard, there is a need to examine prevailing design approaches, weigh their benefits and challenges toward implementation, and recommend a path forward that synthesizes the needs of this complex stakeholder group.

OBJECTIVE

In this review, we aimed to study prominent digital health intervention design approaches that mediate the digital health space. In doing so, we sought to examine the origins, perceived benefits, contrasting nuances, challenges, and typical use-case scenarios of each methodology.

METHODS

A narrative review of digital health design approaches was performed between September 2020 and April 2021 by referencing keywords such as "digital health design," "mHealth design," "e-Health design," "agile health," and "agile healthcare." The studies selected after screening were those that discussed the design and implementation of digital health design approaches. A total of 120 studies were selected for full-text review, of which 62 (51.6%) were selected for inclusion in this review.

RESULTS

A review identifying the 5 overarching digital health design approaches was compiled: user-centered design, person-based design, human-centered design, patient-centered design, and patient-led design. The findings were synthesized in a narrative structure discussing the origins, advantages, disadvantages, challenges, and potential use-case scenarios.

CONCLUSIONS

Digital health is experiencing the growing pains of rapid expansion. Currently, numerous design approaches are being implemented to harmonize the needs of a complex stakeholder group. Whether the end user is positioned as a person, patient, or user, the challenge to synthesize the constraints and affordances of both digital design and health care, built equally around user satisfaction and clinical efficacy, remains paramount. Further research that works toward a transdisciplinarity in digital health may help break down friction in this field. Until digital health is viewed as a hybridized industry with unique requirements rather than one with competing interests, the nuances that each design approach posits will be difficult to realize in a real-world context. We encourage the collaboration of digital and health experts within hybrid design teams, through all stages of intervention design, to create a better digital health culture and design ethos.

A Comprehensive Literature Search of Digital Health Technology Use in Neurological Conditions: Review of Digital Tools to Promote Self-management and Support

BACKGROUND

The use of digital health technology to promote and deliver postdiagnostic care in neurological conditions is becoming increasingly common. However, the range of digital tools available across different neurological conditions and how they facilitate self-management are unclear.

OBJECTIVE

This review aims to identify digital tools that promote self-management in neurological conditions and to investigate their underlying functionality and salient clinical outcomes.

METHODS

We conducted a search of 6 databases (ie, CINAHL, EMBASE, MEDLINE, PsycINFO, Web of Science, and the Cochrane Review) using free text and equivalent database-controlled vocabulary terms.

RESULTS

We identified 27 published articles reporting 17 self-management digital tools. Multiple sclerosis (MS) had the highest number of digital tools followed by epilepsy, stroke, and headache and migraine with a similar number, and then pain. The majority were aimed at patients with a minority for carers. There were 5 broad categories of functionality promoting self-management: (1) knowledge and understanding; (2) behavior modification; (3) self-management support; (4) facilitating communication; and (5) recording condition characteristics. Salient clinical outcomes included improvements in self-management, self-efficacy, coping, depression, and fatigue.

CONCLUSIONS

There now exist numerous digital tools to support user self-management, yet relatively few are described in the literature. More research is needed to investigate their use, effectiveness, and sustainability, as well as how this interacts with increasing disability, and their integration within formal neurological care environments.

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.

Leveraging the Potential of Digital Technology for Better Individualized Treatment of Parkinson's Disease

Recent years have witnessed a strongly increasing interest in digital technology within medicine (sensor devices, specific smartphone apps) and specifically also neurology. Quantitative measures derived from digital technology could provide Digital Biomarkers (DMs) enabling a quantitative and continuous monitoring of disease symptoms, also outside clinics. This includes the possibility to continuously and sensitively monitor the response to treatment, hence opening the opportunity to adapt medication pathways quickly. In addition, DMs may in the future allow early diagnosis, stratification of patient subgroups and prediction of clinical outcomes. Thus, DMs could complement or in certain cases even replace classical examiner-based outcome measures and molecular biomarkers measured in cerebral spinal fluid, blood, urine, saliva, or other body liquids. Altogether, DMs could play a prominent role in the emerging field of precision medicine. However, realizing this vision requires dedicated research. First, advanced data analytical methods need to be developed and applied, which extract candidate DMs from raw signals. Second, these candidate DMs need to be validated by (a) showing their correlation to established clinical outcome measures, and (b) demonstrating their diagnostic and/or prognostic value compared to established biomarkers. These points again require the use of advanced data analytical methods, including machine learning. In addition, the arising ethical, legal and social questions associated with the collection and processing of sensitive patient data and the use of machine learning methods to analyze these data for better individualized treatment of the disease, must be considered thoroughly. Using Parkinson's Disease (PD) as a prime example of a complex multifactorial disorder, the purpose of this article is to critically review the current state of research regarding the use of DMs, discuss open challenges and highlight emerging new directions.

Rapid development of an integrated remote programming platform for neuromodulation systems through the biodesign process

Treating chronic symptoms for pain and movement disorders with neuromodulation therapies involves fine-tuning of programming parameters over several visits to achieve and maintain symptom relief. This, together with challenges in access to trained specialists, has led to a growing need for an integrated wireless remote care platform for neuromodulation devices. In March of 2021, we launched the first neuromodulation device with an integrated remote programming platform. Here, we summarize the biodesign steps taken to identify the unmet patient need, invent, implement, and test the new technology, and finally gain market approval for the remote care platform. Specifically, we illustrate how agile development aligned with the evolving regulatory requirements can enable patient-centric digital health technology in neuromodulation, such as the remote care platform. The three steps of the biodesign process applied for remote care platform development are: (1) Identify, (2) Invent, and (3) Implement. First, we identified the unmet patient needs through market research and voice-of-customer (VOC) process. Next, during the concept generation phase of the invention step, we integrated the results from the VOC into defining requirements for prototype development. Subsequently, in the concept screening phase, ten subjects with PD participated in a clinical pilot study aimed at characterizing the safety of the remote care prototype. Lastly, during the implementation step, lessons learned from the pilot experience were integrated into final product development as new features. Following final product development, we completed usability testing to validate the full remote care system and collected preliminary data from the limited market release experience. The VOC data, during prototype development, helped us identify thresholds for video quality and needs priorities for clinicians and patients. During the pilot study, one subject reported anticipated remote-care-related adverse events that were resolved without sequelae. For usability analysis following final product development, the failure rates for task completion for both user groups were about 1%. Lastly, during the initial 4 weeks of the limited market release experience, a total of 858 remote care sessions were conducted with a 93% success rate. Overall, we developed a remote care platform by adopting a user-centric approach. Although the system intended to address pre-COVID19 challenges associated with disease management, the unforeseen overlap of the study with the pandemic elevated the importance of such a system and an innovative development process enabled us to advance a patient-centric platform to gain regulatory approval and successfully launch the remote care platform to market.

A Long Way to Go: Patient Perspectives on Digital Health for Parkinson's Disease

Digital health promises to improve healthcare, health, and wellness through the use of digital technologies. The purpose of this commentary is to review and discuss the field of digital health for Parkinson’s disease (PD) focusing on the needs, expectations, and wishes of people with PD (PwP). Our analysis shows that PwP want to use digital technologies to actively manage the full complexity of living with PD on an individual level, including the unpredictability and variability of the condition. Current digital health projects focusing on PD, however, does not live up to the expectations of PwP. We conclude that for digital health to reach its full potential, the right of PwP to access their own data needs to be recognised, PwP should routinely receive personalised feedback based on their data, and active involvement of PwP as an equal partner in digital health development needs to be the norm.

Domotics, Smart Homes, and Parkinson's Disease

Technology has an increasing presence and role in the management of Parkinson’s disease. Whether embraced or rebuffed by patients and clinicians, this is an undoubtedly growing area. Wearable sensors have received most of the attention so far. This review will focus on technology integrated into the home setting; from fixed sensors to automated appliances, which are able to capture information and have the potential to respond in an unsupervised manner. Domotics also have the potential to provide ‘real world’ context to kinematic data and therapeutic opportunities to tackle challenging motor and non-motor symptoms. Together with wearable technology, domotics have the ability to gather long-term data and record discrete events, changing the model of the cross-sectional outpatient assessment. As clinicians, our ultimate goal is to maximise quality of life, promote autonomy, and personalise care. In these respects, domotics may play an essential role in the coming years.

Personalizing decision-making for persons with Parkinson's disease: where do we stand and what to improve?

Background

The large variety in symptoms and treatment effects across different persons with Parkinson’s disease (PD) warrants a personalized approach, ensuring that the best decision is made for each individual. We aimed to further clarify this process of personalized decision-making, from the perspective of medical professionals.

Methods

We audio-taped 52 consultations with PD patients and their neurologist or PD nurse-specialist, in 6 outpatient clinics. We focused coding of the transcripts on which decisions were made and on if and how decisions were personalized. We subsequently interviewed professionals to elaborate on how and why decisions were personalized, and which decisions would benefit most from a more personalized approach.

Results

Most decisions were related to medication, referral or lifestyle. Professionals balanced clinical factors, including individual (disease-) characteristics, and non-clinical factors, including patients’ preference, for each type of decision. These factors were often not explicitly discussed with the patient. Professionals experienced difficulties in personalizing decisions, mostly because evidence on the impact of characteristics of an individual patient on the outcome of the decision is unavailable. Categories of decisions for which professionals emphasized the importance of a more personalized perspective include choices not only for medication and advanced treatments, but also for referrals, lifestyle and diagnosis.

Conclusions

Clinical decision-making is a complex process, influenced by many different factors that differ for each decision and for each individual. In daily practice, it proves difficult to tailor decisions to individual (disease-) characteristics, probably because sufficient evidence on the impact of these individual characteristics on outcomes is lacking.

Implementation fidelity of a nurse-led RCT-tested complex intervention, care coordination for health promotion and activities in Parkinson's disease (CHAPS) in meeting challenges in care management

BACKGROUND

Parkinson's disease (PD) complexity poses challenges for individuals with Parkinson's, providers, and researchers. A recent multisite randomized trial of a proactive, telephone-based, nurse-led care management intervention - Care Coordination for Health Promotion and Activities in Parkinson's Disease (CHAPS) - demonstrated improved PD care quality. Implementation details and supportive stakeholder feedback were subsequently published. To inform decisions on dissemination, CHAPS Model components require evaluations of their fidelity to the Chronic Care Model and to their implementation. Additionally, assessment is needed on whether CHAPS addresses care challenges cited in recent literature.

METHODS

These analyses are based on data from a subset of 140 intervention arm participants and other CHAPS data. To examine CHAPS Model fidelity, we identified CHAPS components corresponding to the Chronic Care Model's six essential elements. To assess implementation fidelity of these components, we examined data corresponding to Hasson's modified implementation fidelity framework. Finally, we identified challenges cited in current Parkinson's care management literature, grouped these into themes using open card sorting techniques, and examined CHAPS data for evidence that CHAPS met these challenges.

RESULTS

All Chronic Care Model essential elements were addressed by 17 CHAPS components, thus achieving CHAPS Model fidelity. CHAPS implementation fidelity was demonstrated by adherence to content, frequency, and duration with partial fidelity to telephone encounter frequency. We identified potential fidelity moderators for all six of Hasson's moderator types. Through card sorting, four Parkinson's care management challenge themes emerged: unmet needs and suggestions for providers (by patient and/or care partner), patient characteristics needing consideration, and standardizing models for Parkinson's care management. CHAPS activities and stakeholder perceptions addressed all these themes.

CONCLUSIONS

CHAPS, a supportive nurse-led proactive Parkinson's care management program, improved care quality and is designed to be reproducible and supportive to clinicians. Findings indicated CHAPS Model fidelity occurred to the Chronic Care Model and fidelity to implementation of the CHAPS components was demonstrated. Current Parkinson's care management challenges were met through CHAPS activities. Thus, dissemination of CHAPS merits consideration by those responsible for implementing changes in clinical practice and reaching people in need.

TRIAL REGISTRATION

ClinicalTrials.gov as NCT01532986 , registered on January 13, 2012.

Levodopa-Induced Dyskinesia in Parkinson Disease Specifically Associates With Dopaminergic Depletion in Sensorimotor-Related Functional Subregions of the Striatum

PURPOSE

To determine whether the development of levodopa-induced dyskinesia (LID) in Parkinson disease (PD) specifically relates to dopaminergic depletion in sensorimotor-related subregions of the striatum.

METHODS

Our primary study sample consisted of 185 locally recruited PD patients, of which 73 (40%) developed LID. Retrospective 123I-FP-CIT SPECT data were used to quantify the specific dopamine transporter (DAT) binding ratio within distinct functionally defined striatal subregions related to limbic, executive, and sensorimotor systems. Regional DAT levels were contrasted between patients who developed LID (PD + LID) and those who did not (PD-LID) using analysis of covariance models controlled for demographic and clinical features. For validation of the findings and assessment of the evolution of LID-associated DAT changes from an early disease stage, we also studied serial 123I-FP-CIT SPECT data from 343 de novo PD patients enrolled in the Parkinson Progression Marker's Initiative using mixed linear model analysis.

RESULTS

Compared with PD-LID, DAT level reductions in PD + LID patients were most pronounced in the sensorimotor striatal subregion (F = 5.99, P = 0.016) and also significant in the executive-related subregion (F = 5.30, P = 0.023). In the Parkinson Progression Marker's Initiative cohort, DAT levels in PD + LID (n = 161, 47%) were only significantly reduced compared with PD-LID in the sensorimotor striatal subregion (t = -2.05, P = 0.041), and this difference was already present at baseline and remained largely constant over time.

CONCLUSION

Measuring DAT depletion in functionally defined sensorimotor-related striatal regions of interest may provide a more sensitive tool to detect LID-associated dopaminergic changes at an early disease stage and could improve individual prognosis of this common clinical complication in PD.

Quadruple Decision Making for Parkinson's Disease Patients: Combining Expert Opinion, Patient Preferences, Scientific Evidence, and Big Data Approaches to Reach Precision Medicine

Clinical decision making for Parkinson’s disease patients is supported by a combination of three distinct information resources: best available scientific evidence, professional expertise, and the personal needs and preferences of patients. All three sources have clear value but also share several important limitations, mainly regarding subjectivity, generalizability and variability. For example, current scientific evidence, especially from controlled clinical trials, is often based on selected study populations, making it difficult to translate the outcome to the care for individual patients in everyday clinical practice. Big data, including data from real-life unselected Parkinson populations, can help to bridge this information gap. Fine-grained patient profiles created from big data have the potential to aid in identifying therapeutic approaches that will be most effective given each patient’s individual characteristics, which is particularly important for a disorder characterized by such tremendous interindividual variability as Parkinson’s disease. In this viewpoint, we argue that big data approaches should be acknowledged and harnessed, not to replace existing information resources, but rather as a fourth and complimentary source of information in clinical decision making, helping to represent the full complexity of individual patients. We introduce the ‘quadruple decision making’ model and illustrate its mode of action by showing how this can be used to pursue precision medicine for persons living with Parkinson’s disease.

Validation of Inertial Sensing-Based Wearable Device for Tremor and Bradykinesia Quantification

Neurologists judge the severity of Parkinsonian motor symptoms according to clinical scales, and their judgments exist inconsistent because of differences in clinical experience. Correspondingly, inertial sensing-based wearable devices (ISWDs) produce objective and standardized quantifications. However, ISWDs indirectly quantify symptoms by parametric modeling of angular velocities and linear accelerations nd trained by the judgments of several neurologists through supervised learning algorithms. Hence, the ISWD outputs are biased along with the scores provided by neurologists. To investigate the effectiveness ISWDs for Parkinsonian symptoms quantification, technical verification and clinical validation of both tremor and bradykinesia quantification methods were carried out. A total of 45 Parkinson's disease patients and 30 healthy controls performed the tremor and finger-tapping tasks, which were tracked simultaneously by an ISWD and a 6-axis high-precision electromagnetic tracking system (EMTS). The Unified Parkinson's Disease Rating Scale (UPDRS) prescribed parameters obtained from the EMTS, which directly provides linear and rotational displacements, were compared with the scores provided by both the ISWD and seven neurologists. EMTS-based parameters were regarded as the ground truth and were employed to train several common machine learning (ML) algorithms, i.e., support vector machine (SVM), k-nearest neighbors (KNN), and random forest (RF) algorithms. Inconsistency among the scores provided by the neurologists was proven. Besides, the quantification performance (sensitivity, specificity, and accuracy) of the ISWD employed with ML algorithms were better than that of the neurologists. Furthermore, EMTS can be utilized to both modify the quantification algorithms of ISWDs and improve the assessment skills of young neurologists.

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.

Findings in Chinese Patients With Parkinson's Disease: A Content Analysis From the SML Study

Social media listening (SML) is a new process for obtaining information from social media platforms to generate insights into users' experiences and has been used to analyze discussions about a multitude of diseases. To understand Parkinson's disease patients' unmet needs and optimize communication between doctors and patients, social media listening was performed to investigate concerns in Chinese patients. A comprehensive search of publicly available social media platforms with Chinese-language content posted between January 2005 and April 2019 in mainland China was performed using defined Parkinson's disease-related terms. After multiple steps of machine screening were performed, a series of posts were derived. The content was summarized and classified manually to analyze and map psychological insights, and descriptive statistics were applied to aggregate findings. A total of 101,899 patient-related posts formed the basis of this study. The topics mainly focused on motor symptoms (n = 54,983), choice of pharmaceutical drugs (n = 45,203) and non-motor symptoms (n = 44,855). The most common symptoms mentioned were tremor (54.5%), pain (22.9%), and rigidity (22.1%). Psychological burden (51%) and work/social burden (48%) were the most concerning burdens for patients and their families. The compound levodopa (43%) and dopamine agonists (23%) were the most common options for the patients, while concerns about new-generation anti-Parkinson's disease medication increased. The portraits of patients suggested varying characteristics across different periods and advocate for personalized service from doctors. In the management of patients, it is imperative to plan individualized therapy and education strategies as well as strategies for social support.

Stakeholder perceptions of components of a Parkinson disease care management intervention, care coordination for health promotion and activities in Parkinson's disease (CHAPS)

BACKGROUND

A recent nurse-led proactive care management intervention, Care Coordination for Health Promotion and Activities in Parkinson Disease (CHAPS), improved care quality when compared to usual care in a randomized controlled trial. Therefore, stakeholder (patient participants, nurse care managers, and Parkinson disease (PD) specialists) perceptions of key intervention components merit evaluation to inform decisions about dissemination.

METHODS

This multi-site study occurred in five southwest United States Veterans Health Administration medical centers. Stakeholders were surveyed on their perceptions of CHAPS including the CHAPS Assessment, CHAPS nurse care managers, the Siebens Domain Management Model™ (a practical clinical model), and the Siebens Health Care Notebook (Notebook) (self-care tool). Participants' electronic medical records were abstracted for perceptions of the Notebook. Statistical analysis software was used to provide summary statistics; open card sorting methodology was used to identify themes and attributes in qualitative data including usability of some components.

RESULTS

Participants, overall, highly rated their medication self-management, acknowledged some challenges with the CHAPS self-care tools, reported knowledge of PD specialist follow-up and PD red flags, and rated CHAPS nurse care managers as helpful. Nurse care manager responses indicated the CHAPS Assessment and Program highly facilitated care of their patients. Most all PD specialists would refer other patients to CHAPS. Nurse care manager and PD specialist responses indicated improved participant management of their PD. Three themes emerged in participant perceptions of the Notebook: Notebook Assets (e.g., benefits and features-liked); Deferring Notebook Review (e.g., no time to review); and Reasons for Not Using (e.g., participant preference). Shared attributes regarding the Siebens Domain Management Model and Notebook usability, reported by nurse care managers, were user-friendly, person/patient-centered, and organized. Some challenges to their use were also reported.

CONCLUSIONS

Overall, stakeholder perceptions of the proactive nurse-led CHAPS intervention indicated its value in the care of individuals with PD. Responses about the CHAPS Assessment, Siebens Domain Management Model, and Notebook self-care tool signified their usefulness. Stakeholders' constructive suggestions indicated their engagement in CHAPS. These findings support CHAPS dissemination and contribute to research in care management.

TRIAL REGISTRATION

ClinicalTrials.gov as NCT01532986 , registered on January 13, 2012.

[Care of patients with Parkinson's disease in Germany: status quo and perspectives as reflected in the digital transition]

Die Parkinson-Krankheit als chronische neurodegenerative Erkrankung bedarf eines engen Zusammenspiels verschiedener Fachdisziplinen, um eine bestmögliche Lebensqualität der Patienten zu gewährleisten. Ein immer wieder identifiziertes Problem ist die insuffiziente Kommunikation zwischen den Protagonisten (z. B. „caregiver“, Ärzte und Therapeuten), insbesondere an den Sektorengrenzen. Die aktuellen Prozess- und Versorgungsketten der Parkinson-Krankheit bilden aber auch aufgrund struktureller Hürden bisher keine gelungene sektorenübergreifende Versorgung ab. Vor dem Hintergrund des neuen Digitale-Versorgung-Gesetzes (DVG) und den damit erstmalig rückfinanzierten, digitalen Gesundheitsanwendungen (DiGAs) können sich nun erstmals innovative, digitale Versorgungs- und Kommunikationsstrukturen etablieren und haben das Potenzial, damit die Versorgung chronischer Erkrankungen, wie z. B. der Parkinson-Krankheit, umfassend zu verändern. Beispiele und Anwendungsszenarien werden in diesem Übersichtsartikel vorgestellt sowie kritisch diskutiert.

[The history of Freezing-of-gait in Parkinson's disease - from phenomena to symptom]

The background of the freezing-of-gait (FOG) phenomenon in Parkinson's syndrome is presented in this review. The following issues are addressed: characterization of the symptom freezing and its subtypes that challenge standardized diagnostic procedures; available assessment methods generating freezing-related parameters that not only support clinical studies but can also be applied in everyday care, and current therapy options. FOG exists in different subtypes, and clinical and diagnostic definitions are limited by subjective characterization and semi-standardized tests. FOG-specific drug options are not existing, apart from the optimization of dopaminergic medication, which may also be due to the poor discriminatory power of standardized diagnostics. This is also true for deep brain stimulation. Both of these therapeutic options may be due not only to the complex neural network alterations as a motor-control correlate of FOG, but also because of challenging diagnostic assessments methodologies. Innovative, wearable, sensor-based diagnostic strategies are currently being developed, and supportive therapies using tools and technologies focusing on 'cueing' are becoming increasingly well accepted. Even though high level evidence is missing, they provide a helpful treatment option for individualized therapy. It can be assumed that these options will become particularly popular due to technological progress and likely alter the everyday treatment challenges faced by doctors and therapists.

Effects of an Innovative Telerehabilitation Intervention for People With Parkinson's Disease on Quality of Life, Motor, and Non-motor Abilities

Parkinson's disease (PD) often leads to multifactorial motor and non-motor disabilities with resultant social restrictions. Continuity of care in this pathology, including a tailored home rehabilitation, is crucial to improve or maintain the quality of life for patients. The aim of this multicenter study was to test in a pilot sample of PD patients the efficiency and efficacy of the Human Empowerment Aging and Disability (HEAD) program. The virtual reality HEAD program was administered in two consecutive phases: (1) in clinic (ClinicHEAD, 12 45-minutes sessions, 3 sessions/week); (2) at home (HomeHEAD, 60 45-minutes sessions, 5 sessions/week). Thirty-one PD outpatients were enrolled [mean age (SD) = 66.84 (9.13)]. All patients performed ClinicHEAD, and after allocation (ratio 1:2) were assigned to the HomeHEAD or the Usual Care (UC) group. Motor, cognitive and behavioral outcome measures were assessed at enrollment (T0), at hospital discharge (T1), at 4 (T2) and 7 (T3) months after baseline. After ClinicHEAD (T1 vs. T0 comparison) a significant (p < 0.05) improvement in functional mobility, balance, upper limb mobility, global cognitive function, memory, quality of life and psychological well-being was observed. After the HomeHEAD intervention there was an additional enhancement for upper limb mobility. At T3 follow-up, the UC group that did not continue the HEAD program at home showed a worsening with respect to the HomeHEAD group in balance and functional mobility. Furthermore, in the HomeHEAD group, a positive association was observed between adherence, mental and physical health (SF-12). A trend was also registered between adherence and positive affect. The digital health patient-tailored rehabilitation program resulted in improving motor and non-motor abilities and quality of life in clinical setting, enhancing the motor function in telerehabilitation at home, and maintaining the non-motor abilities and quality of life at follow-up. In the near future, people with PD can be supported also at home with individualized rehabilitation strategies for a better quality of life and wellbeing along with lower costs for society.

Evaluation of HealthPathways: an appraisal of usage, experiences and opinions of healthcare professionals in Australia and New Zealand

Objectives HealthPathways, pioneered in Canterbury, New Zealand, in 2008, is a web-based tool designed to promote health care integration and patient management in primary care and to reduce fragmentation in the delivery of health services. This cross-sectional study evaluated the utilisation and perceptions of this tool among health professionals in Australia and New Zealand. Methods A cross-sectional survey was administered online through Research Electronic Data Capture (REDCap) to general practitioners (GPs), practice nurses and managers, nurse practitioners, specialist and community nurses, hospital clinicians, nurses, managers, and allied health professionals between April and September 2018. The frequency of HealthPathways use in the previous month was modelled as an ordered response using an ordered logistic regression model after adjusting for the possible effects of sex, age, years in clinical practice, location and time spent in practice. Results Health professionals perceived HealthPathways to be useful in primary care management and referral, as well as in the prereferral treatment of patients. GPs in New Zealand, New South Wales and Victoria were 73%, 47% and 27% more likely to have used HealthPathways ≥10 times in the previous month respectively. Conclusion The results suggest that HealthPathways is having a positive effect on healthcare systems in New Zealand and Australia. However, differences in uptake suggests the need for focused implementation, integration into eReferral software and expanding the tool to medical students, registrars, allied health professionals and potentially patients to encourage behavioural change. What is known about the topic? Early evaluations suggest that HealthPathways is a useful tool for health professionals, although uptake and utilisation may be limited. However, there is no comparative evidence regarding uptake and implementation of the tool. What does the paper add? This study is among the first to provide a comparative narrative of the literature assessing the implementation and uptake of HealthPathways across Australia and New Zealand. It is also among the first to compare the perceptions of allied health professionals in the use of HealthPathways across Australia and New Zealand. What are the implications for practitioners? The results of this study suggest the need for focused implementation, integration into eReferral software and expanding the tool to medical students, registrars, allied health professionals and potentially patients to encourage behavioural change.

A perspective of private health care providers in the state of Madhya Pradesh on adopting key strategies of the India hypertension control initiative

The India Hypertension Control Initiative (IHCI) has been implemented in public health facilities. This study assessed the perspective of private physicians (PPs) on adopting the core strategies of the IHCI in Bhopal district of Madhya Pradesh. A semi-structured interview was purposely applied to 30 PPs to obtain their opinions on standardized hypertension treatment protocols, patient-centered services, and easy-to-use information system in their private practices. Verbatim data were recorded and analyzed thematically. Only 11 PPs followed the state hypertension treatment protocol. Among the remaining 19 PPs, the major reasons for not adopting protocol were (1) limited availability of single component hypertension drugs, (2) preferences for fixed dose combinations (FDCs), and (3) fear of either losing patients due to a lack of immediate blood pressure control or causing drug-related adverse effects. None of the interviewed doctors had resources to provide patient-centered care and use a digital health information system. Overall, the interviewed doctors identified that free supply of hypertension treatment protocol drugs, inclusion of FDCs in treatment protocol, increasing number of staff for follow-up visits, and patient education, IT-based solutions for patient records, employee incentives, and need for national data sharing policies are the key actions to accelerate the adoption of IHCI strategies in the private sector. This exploratory qualitative study suggests that engagement of private sector in the IHCI is feasible. Plans to expand the IHCI to the private sector should consider ensuring the wider availability of hypertension treatment protocol drugs and developing a simple user-friendly digital platform for patient monitoring.

Recommendations for Standards of Network Care for Patients with Parkinson's Disease in Germany

Although our understanding of Parkinson’s disease (PD) has improved and effective treatments are available, caring for people with PD remains a challenge. The large heterogeneity in terms of motor symptoms, nonmotor symptoms, and disease progression makes tailored individual therapy and individual timing of treatment necessary. On the other hand, only limited resources are available for a growing number of patients, and the high quality of treatment cannot be guaranteed across the board. At this point, networks can help to make better use of resources and improve care. The working group PD Networks and Integrated Care, part of the German Parkinson Society, is entrusted to convene clinicians, therapists, nurses, researchers, and patients to promote the development of PD networks. This article summarizes the work carried out by the working group PD Networks and Integrated Care in the development of standards of network care for patients with PD in Germany.

Smartphone-Based Estimation of Item 3.8 of the MDS-UPDRS-III for Assessing Leg Agility in People With Parkinson's Disease

Goal: In this paper we investigated the use of smartphone sensors and Artificial Intelligence techniques for the automatic quantification of the MDS-UPDRS-Part III Leg Agility (LA) task, representative of lower limb bradykinesia. Methods: We collected inertial data from 93 PD subjects. Four expert neurologists provided clinical evaluations. We employed a novel Artificial Neural Network approach in order to get a continuous output, going beyond the MDS-UPDRS score discretization. Results: We found a Pearson correlation of 0.92 between algorithm output and average clinical score, compared to an inter-rater agreement index of 0.88. Furthermore, the classification error was less than 0.5 scale point in about 80% cases. Conclusions: We proposed an objective and reliable tool for the automatic quantification of the MDS-UPDRS Leg Agility task. In perspective, this tool is part of a larger monitoring program to be carried out during activities of daily living, and managed by the patients themselves.

[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.

Probiotics for Parkinson's Disease

Parkinson’s disease (PD) is a complex neurological disorder classically characterized by impairments in motor system function associated with loss of dopaminergic neurons in the substantia nigra. After almost 200 years since the first description of PD by James Parkinson, unraveling the complexity of PD continues to evolve. It is now recognized that an interplay between genetic and environmental factors influences a diverse range of cellular processes, reflecting on other clinical features including non-motor symptoms. This has consequently highlighted the extensive value of early clinical diagnosis to reduce difficulties of later stage management of PD. Advancement in understanding of PD has made remarkable progress in introducing new tools and strategies such as stem cell therapy and deep brain stimulation. A link between alterations in gut microbiota and PD has also opened a new line. Evidence exists of a bidirectional pathway between the gastrointestinal tract and the central nervous system. Probiotics, prebiotics and synbiotics are being examined that might influence gut-brain axis by altering gut microbiota composition, enteric nervous system, and CNS. This review provides status on use of probiotics for PD. Limitations and future directions will also be addressed to promote further research considering use of probiotics for PD.

α-Synuclein in Parkinson's disease: causal or bystander?

Parkinson's disease (PD) comprises a spectrum of disorders with differing subtypes, the vast majority of which share Lewy bodies (LB) as a characteristic pathological hallmark. The process(es) underlying LB generation and its causal trigger molecules are not yet fully understood. α-Synuclein (α-syn) is a major component of LB and SNCA gene missense mutations or duplications/triplications are causal for rare hereditary forms of PD. As typical sporadic PD is associated with LB pathology, a factor of major importance is the study of the α-syn protein and its pathology. α-Syn pathology is, however, also evident in multiple system atrophy (MSA) and Lewy body disease (LBD), making it non-specific for PD. In addition, there is an overlap of these α-synucleinopathies with other protein-misfolding diseases. It has been proven that α-syn, phosphorylated tau protein (pτ), amyloid beta (Aβ) and other proteins show synergistic effects in the underlying pathogenic mechanisms. Multiple cell death mechanisms can induce pathological protein-cascades, but this can also be a reverse process. This holds true for the early phases of the disease process and especially for the progression of PD. In conclusion, while rare SNCA gene mutations are causal for a minority of familial PD patients, in sporadic PD (where common SNCA polymorphisms are the most consistent genetic risk factor across populations worldwide, accounting for 95% of PD patients) α-syn pathology is an important feature. Conversely, with regard to the etiopathogenesis of α-synucleinopathies PD, MSA and LBD, α-syn is rather a bystander contributing to multiple neurodegenerative processes, which overlap in their composition and individual strength. Therapeutic developments aiming to impact on α-syn pathology should take this fact into consideration.