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Research Items (863)
Background Parkinson’s disease is a complex neurological disorder characterized by a variety of motor- as well as non-motor symptoms. Video-based technology (using continuous home monitoring) may bridge the gap between the fragmented in-clinic observations and the need for a comprehensive understanding of the progression and fluctuation of disease symptoms. However, continuous monitoring can be intrusive, raising questions about feasibility as well as potential privacy violation. Methods We used a grounded theory approach in which we performed semi-structured interviews to explore the opinion of Parkinson’s patients on home-based video recording used for vision-based movement analysis. Results Saturation was reached after sixteen interviews. Three first–level themes were identified that specify the conditions required to perform continuous video monitoring: Camera recording (e.g. being able to turn off the camera), privacy protection (e.g. patient’s behaviour, patient’s consent, camera location) and perceived motivation (e.g. contributing to science or clinical practice). Conclusion Our findings show that Parkinson patients’ perception of continuous, home-based video recording is positive, when a number of requirements are taken into account. This knowledge will enable us to start using this technology in future research and clinical practice in order to better understand the disease and to objectify outcomes in the patients’ own homes.
Freezing of gait, defined as sudden and usually brief episodes of inability to produce effective stepping, often results in falls and is both disabling and common in parkinsonism. In this narrative review, sprung from the 2nd International Workshop on freezing of gait in Leuven, we summarize the latest insights into clinical and methodological challenges for assessing freezing of gait. We also highlight the role of emerging wearable technology to improve the management of this debilitating symptom. © 2019 International Parkinson and Movement Disorder Society
Background The traditional evaluation of gait in the laboratory during structured testing has provided important insights, but is limited by its “snapshot” character and observation in an unnatural environment. Wearables enable monitoring of gait in real-world environments over a week. Initial findings show that in-lab and real-world measures differ. As a step towards better understanding these gaps, we directly compared in-lab usual-walking (UW) and dual-task walking (DTW) to daily-living measures of gait. Methods In-lab gait features (e.g., gait speed, step regularity, and stride regularity) derived from UW and DTW were compared to the same gait features during daily-living in 150 elderly fallers (age: 76.5 ± 6.3 years, 37.6% men). In both settings, features were extracted from a lower-back accelerometer. In the real-world setting, subjects were asked to wear the device for 1 week and pre-processing detected 30-s daily-living walking bouts. A histogram of all walking bouts was determined for each walking feature for each subject and then each subject’s typical (percentile 50, median), worst (percentile 10) and the best (percentile 90) values over the week were determined for each feature. Statistics of reliability were assessed using Intra-Class correlations and Bland-Altman plots. Results As expected, in-lab gait speed, step regularity, and stride regularity were worse during DTW, compared to UW. In-lab gait speed, step regularity, and stride regularity during UW were significantly higher (i.e., better) than the typical daily-living values (p < 0.001) and different (p < 0.001) from the worst and best values. DTW values tended to be similar to typical daily-living values (p = 0.205, p = 0.053, p = 0.013 respectively). ICC assessment and Bland-Altman plots indicated that in-lab values do not reliably reflect the daily-walking values. Conclusions Gait values measured during relatively long (30-s) daily-living walking bouts are more similar to the corresponding values obtained in the lab during dual-task walking, as compared to usual walking. Still, gait performance during most daily-living walking bouts is worse than that measured during usual and dual-tasking in the lab. The values measured in the lab do not reliably reflect daily-living measures. That is, an older adult’s typical daily-living gait cannot be estimated by simply measuring walking in a structured, laboratory setting.
Importance: Patients with Parkinson disease can use a wide variety of strategies to compensate for their gait impairments. Examples include walking while rhythmically bouncing a ball, crossing the legs when walking, or stepping over an inverted cane. An overview and classification of the many available compensation strategies may contribute to understanding their underlying mechanisms and developing focused rehabilitation techniques. Moreover, a comprehensive summary of compensation strategies may help patients by allowing them to select a strategy that best matches their needs and preferences and health care professionals by permitting them to incorporate these into their therapeutic arsenal. To create this overview, this narrative review discusses collected video recordings of patients who spontaneously informed clinicians about the use of self-invented tricks and aids to improve their mobility. Observations: Fifty-nine unique compensation strategies were identified from approximately several hundred videos. Here, these observed strategies are classified into 7 main categories for elaboration on their possible underlying mechanisms. The overarching working mechanisms involve an allocation of attention to gait, the introduction of goal directedness, and the use of motor programs that are less automatized than those used for normal walking. Conclusions and relevance: Overall, these compensation strategies seem to appeal to processes that refer to earlier phases of the motor learning process rather than to a reliance on final consolidation. This review discusses the implications of the various compensation strategies for the management of gait impairment in Parkinson disease.
The neurological examination should always begin before the patient enters the doctor’s office. Movement disorders in particular lend themselves to a spot diagnosis. In today’s busy buzzing world, it seems wasteful not to make use of the various diagnostic clues that can be picked up readily while the patient is still in the waiting room. We present several illustrative examples, drawn from the literature and from our own experience. These are divided according to the different waiting room ‘stages’: the patient sitting in the waiting room, the response on being summoned to enter the consulting room—including rising from the chair, exchanging initial pleasantries and the way of walking. We also discuss the importance of paying attention to the patient’s behaviour, clothing, posture, breathing patterns, facial expression and major gait abnormalities.
We present a 48-year-old woman with Parkinson's disease in whom carbidopa was added to Mucuna pruriens, resulting in marked motor improvement (documented on video and using MDS-UPDRS motor scores). This case report shows that adding a dopa-decarboxylase inhibitor (DDCI) to Mucuna pruriens coud fit well in a personalized approach for patients who are reluctant to start levodopa. Meanwhile, larger trials with a longer follow-up are needed to establish the true effects and tolerability of Mucuna pruriens plus a DDCI.
Dementia and Parkinson's disease are incurable neurological conditions. Patients often experience specific, complex, and varying needs along their disease trajectory. Current management typically employs a multidisciplinary team approach. Recognition is growing that this team approach should also address palliative care issues to optimize quality of life for patient and family caregivers, but it remains unclear how palliative care is best delivered. To inspire future service development and research, we compare the trajectories and conceptualization of palliative care between dementia and Parkinson's disease. Both Parkinson's disease and dementia are characterized by a protracted course, with progressive but fairly insidious development of disability. However, patients with Parkinson's disease may experience relatively stable periods initially but with time, a wide range of debilitating symptoms develops, many of which do not respond well to treatment. Eventually, dementia develops in most Parkinson patients, while motor disability develops in many dementia patients. In both diseases, symptoms such as pain, apathy, sleeping problems, falls, and a high caregiver burden are prevalent. Advance care planning has benefits in terms of being prepared before the disease progresses into a stage with communication problems or severe cognitive impairment. However, for both conditions, the protracted disease trajectories complicate conceptualization of palliative care through different stages of the disease, with pertinent questions such as when to offer what interventions pro-actively. Given the similarities and differences, we should develop palliative approaches that are partially generic and partially disease-specific. These should be integrated seamlessly with disease-specific care. Substantial research is already being performed on dementia palliative care. This may also inform the further development of palliative care for Parkinson's disease, including an evaluation of palliative interventions and services.
Obtaining reliable longitudinal information about everyday functioning from individuals with Parkinson's disease (PD) in natural environments is critical for clinical care and research. Despite advances in mobile health technologies, the implementation of digital outcome measures is hindered by a lack of consensus on the type and scope of measures, the most appropriate approach for data capture (eg, in clinic or at home), and the extraction of timely information that meets the needs of patients, clinicians, caregivers, and health care regulators. The Movement Disorder Society Task Force on Technology proposes the following objectives to facilitate the adoption of mobile health technologies: (1) identification of patient‐centered and clinically relevant digital outcomes; (2) selection criteria for device combinations that offer an acceptable benefit‐to‐burden ratio to patients and that deliver reliable, clinically relevant insights; (3) development of an accessible, scalable, and secure platform for data integration and data analytics; and (4) agreement on a pathway for approval by regulators, adoption into e‐health systems and implementation by health care organizations. We have developed a tentative roadmap that addresses these needs by providing the following deliverables: (1) results and interpretation of an online survey to define patient‐relevant endpoints, (2) agreement on the selection criteria for use of device combinations, (3) an example of an open‐source platform for integrating mobile health technology output, and (4) recommendations for assessing readiness for deployment of promising devices and algorithms suitable for regulatory approval. This concrete implementation guidance, harmonizing the collaborative endeavor among stakeholders, can improve assessments of individuals with PD, tailor symptomatic therapy, and enhance health care outcomes. © 2019 International Parkinson and Movement Disorder Society
Objective: To investigate the diagnostic value of serum neurofilament light chain (NFL) in patients with clear signs of parkinsonism but whose specific diagnosis was yet uncertain. Methods: Serum samples were collected from patients with clear signs of parkinsonism but with uncertain diagnosis at the inclusion. Clinical diagnoses of Parkinson disease (PD) and atypical parkinsonism disorders (APDs) were established after 3 years of follow-up and updated again after a maximum of 12 years in case longer follow-up data were available. Serum NFL was quantified by single molecule array in patients with PD (n = 55) and APD (n = 29, multiple system atrophy = 22, progressive supranuclear palsy = 7) and 53 nonneurologic controls. Results: Serum NFL levels were elevated and differentiated the APD group (mean 23.8 ± 10.3 ng/L) from PD (mean 10.4 ± 4.9 ng/L) and controls (mean 11.5 ± 6.5 ng/L, p < 0.0001) with accuracy levels up to 91% (sensitivity = 86% and specificity = 85%). Serum NFL strongly correlated with CSF NFL levels (r = 0.72, p < 0.0001) in all groups and with age in PD (r = 0.78, p < 0.0001) and controls (r = 0.66, p < 0.0001). In our cohort, the probability of having APD was 76% (positive predictive value) and of having PD 92% (negative predictive value). Conclusion: Serum NFL levels are markedly elevated in APD compared to PD and discriminate APDs from PD with high accuracy. Serum NFL may be a useful clinical biomarker to identify APD, even at stages when clinical symptoms are not yet conclusive. Classification of evidence: This study provides Class II evidence that serum NFL levels accurately discriminate APDs from PD.
A reliable biomarker is needed for accurate and early differentiation between Parkinson's disease (PD) and the various forms of atypical parkinsonism (AP). We used a novel real‐time quaking‐induced conversion (RT‐QuIC) assay to detect alpha‐synuclein (α‐syn) aggregates in cerebrospinal fluid (CSF) of 118 patients with parkinsonism of uncertain clinical etiology and 52 controls. Diagnostic accuracy to distinguish α‐synucleinopathies from non‐α‐synucleinopathies and controls was 84% (sensitivity 75%, specificity 94% (AUC 0.84, 95% CI 0.78‐0.91, p<0.0001), PPV 93%). CSF α‐syn RT‐QuIC could be a useful diagnostic tool to help clinicians differentiate α‐synucleinopathies from other forms of parkinsonism when the clinical picture is uncertain. This article is protected by copyright. All rights reserved.
Non‐manifesting carriers (NMC) of the G2019S mutation in the LRRK2 gene represent an “at risk” group for future development of Parkinson's disease (PD) and have demonstrated task related fMRI changes. However, resting‐state networks have received less research focus, thus this study aimed to assess the integrity of the motor, default mode (DMN), salience (SAL), and dorsal attention (DAN) networks among this unique population by using two different connectivity measures: interregional functional connectivity analysis and Dependency network analysis (DEPNA). Machine learning classification methods were used to distinguish connectivity between the two groups of participants. Forty‐four NMC and 41 non‐manifesting non‐carriers (NMNC) participated in this study; while no behavioral differences on standard questionnaires could be detected, NMC demonstrated lower connectivity measures in the DMN, SAL, and DAN compared to NMNC but not in the motor network. Significant correlations between NMC connectivity measures in the SAL and attention were identified. Machine learning classification separated NMC from NMNC with an accuracy rate above 0.8. Reduced integrity of non‐motor networks was detected among NMC of the G2019S mutation in the LRRK2 gene prior to identifiable changes in connectivity of the motor network, indicating significant non‐motor cerebral changes among populations “at risk” for future development of PD.
Introduction: Although circadian variation of (motor) symptoms in Parkinson disease (PD) patients has been described, it remains unclear what effect seasonal variation may have on non-motor symptoms (NMS). Methods: Cross-sectional retrospective study on 372 consecutive PD patients taking part in the Non-motor Longitudinal International Study at King's College Hospital London between November 2011 and July 2018. Patients were divided into three groups based on their date of assessment, using a simplified seasonal model: group 1: November-February (n = 107); group 2: March-15 June (n = 107); and group 3: 16 June-October (n = 158). Primary outcome was a seasonal difference in NMS scale (NMSS) total scores (higher scores reflecting greater disability). We hypothesized that PD patients exhibit circannual NMS burden patterns. Results: All groups were identical concerning disease onset and duration, HY stage, Levodopa equivalent dose, and gender. There was a seasonal difference in NMSS total scores (p = 0.040), with the highest scores (57.1 ± 42.5) in season 1 (winter months) and the lowest (45.1 ± 34.4) in season 3 (summer months) (p = 0.037). Seasonal differences were observed in NMSS domain 1 (cardiovascular symptoms) (p = 0.011), domain 4 (perceptual problems) (p = 0.017) and domain 9 (miscellaneous symptoms) (p = 0.009). A trend was observed for domain 2 (sleep) (p = 0.057). Conclusion: NMS in PD fluctuate throughout the year, with worsening of symptoms in the winter months compared to the summer months suggestive of dysfunction of the body's master clock, the suprachiasmatic nuclei. Such variations must be accommodated in daily care to ascertain appropriate changes in medication regimes and in clinical trials for the interpretation of outcomes.
Background Levodopa is the main treatment for symptoms of Parkinson’s disease. Determining whether levodopa also has a disease-modifying effect could provide guidance as to when in the course of the disease the treatment with this drug should be initiated. Methods In a multicenter, double-blind, placebo-controlled, delayed-start trial, we randomly assigned patients with early Parkinson’s disease to receive levodopa (100 mg three times per day) in combination with carbidopa (25 mg three times per day) for 80 weeks (early-start group) or placebo for 40 weeks followed by levodopa in combination with carbidopa for 40 weeks (delayed-start group). The primary outcome was the between-group difference in the mean change from baseline to week 80 in the total score on the Unified Parkinson’s Disease Rating Scale (UPDRS; scores range from 0 to 176, with higher scores signifying more severe disease). Secondary analyses included the progression of symptoms, as measured by the UPDRS score, between weeks 4 and 40 and the noninferiority of early initiation of treatment to delayed initiation between weeks 44 and 80, with a noninferiority margin of 0.055 points per week. Results A total of 445 patients were randomly assigned: 222 to the early-start group and 223 to the delayed-start group. The mean (±SD) UPDRS score at baseline was 28.1±11.4 points in the early-start group and 29.3±12.1 points in the delayed-start group. The change in UPDRS score from baseline to week 80 was −1.0±13.1 points and −2.0±13.0 points, respectively (difference, 1.0 point; 95% confidence interval [CI], −1.5 to 3.5; P=0.44); this finding of no significant between-group difference at week 80 implies that levodopa had no disease-modifying effect. Between weeks 4 and 40, the rate of progression of symptoms, as measured in UPDRS points per week, was 0.04±0.23 in the early-start group and 0.06±0.34 in the delayed-start group (difference, −0.02; 95% CI, −0.07 to 0.03). The corresponding rates between weeks 44 and 80 were 0.10±0.25 and 0.03±0.28 (difference, 0.07; two-sided 90% CI, 0.03 to 0.10); the difference in the rate of progression between weeks 44 and 80 did not meet the criterion for noninferiority of early receipt of levodopa to delayed receipt. The rates of dyskinesia and levodopa-related fluctuations in motor response did not differ significantly between the two groups. Conclusions Among patients with early Parkinson’s disease who were evaluated over the course of 80 weeks, treatment with levodopa in combination with carbidopa had no disease-modifying effect. (Funded by the Netherlands Organization for Health Research and Development and others; LEAP Current Controlled Trials number, ISRCTN30518857.)
BACKGROUND AND PURPOSE: Dual-task interventions show positive effects in people with Parkinson disease (PD), but it remains unclear which factors determine the size of these benefits. As a secondary analysis of the DUALITY trial, the aim of this study was to assess the determinants of the effect size after 2 types of dual-task practice. METHODS: We randomly allocated 121 participants with PD to receive either integrated or consecutive dual-task training. Dual-task walking performance was assessed during (i) a backward digit span task (digit), (ii) an auditory Stroop task (Stroop), and (iii) a functional mobile phone task. Baseline descriptive, motor, and cognitive variables were correlated with the change in dual-task gait velocity after the intervention. Factors correlated with the change in dual-task gait velocity postintervention (P < 0.20) were entered into a stepwise forward multiple linear regression model. RESULTS: Lower dual-task gait velocity and higher cognitive capacity (Scales for Outcomes in Parkinson's Disease-Cognition [ScopaCog]) at baseline were related to larger improvements in dual-task gait velocity after both integrated and consecutive dual-task training for all 3 tasks (β[gait] = -0.45, β[ScopaCog] = 0.34, R = 0.23, P < 0.001, for digit; β[gait] = -0.52, β[ScopaCog] = 0.29, R = 0.26, P < 0.001, for Stroop; and β[gait] = -0.40, β[ScopaCog] = 0.30, R = 0.18, P < 0.001, for mobile phone task). DISCUSSION AND CONCLUSIONS: Participants with PD who showed a slow dual-task gait velocity and good cognitive functioning at baseline benefited most from the dual-task training, irrespective of the type of training and type of dual-task outcome.Video Abstract available for more insights from the authors (see Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A242).
Introduction: Recent work suggests that wearables can augment conventional measures of Parkinson's disease (PD). We evaluated the relationship between conventional measures of disease and motor severity (e.g., MDS-UPDRS part III), laboratory-based measures of gait and balance, and daily-living physical activity measures in patients with PD. Methods: Data from 125 patients (age: 71.7 ± 6.5 years, Hoehn and Yahr: 1–3, 60.5% men) were analyzed. The MDS-UPDRS-part III was used as the gold standard of motor symptom severity. Gait and balance were quantified in the laboratory. Daily-living gait and physical activity metrics were extracted from an accelerometer worn on the lower back for 7 days. Results: In multivariate analyses, daily-living physical activity and gait metrics, laboratory-based balance, demographics and subject characteristics together explained 46% of the variance in MDS-UPDRS-part III scores. Daily-living measures accounted for 62% of the explained variance, laboratory measures 30%, and demographics and subject characteristics 7% of the explained variance. Conversely, demographics and subject characteristics, laboratory-based measures of gait symmetry, and motor symptom severity together explained less than 30% of the variance in total daily-living physical activity. MDS-UPDRS-part III scores accounted for 13% of the explained variance, i.e., <4% of all the variance in total daily-living activity. Conclusions: Our findings suggest that conventional measures of motor symptom severity do not strongly reflect daily-living activity and that daily-living measures apparently provide important information that is not captured in a conventional one-time, laboratory assessment of gait, balance or the MDS-UPDRS. To provide a more complete evaluation, wearable devices should be considered.
Introduction: Parkinson’s disease (PD) is a chronic multisystem disorder that causes a wide variety of motor and non-motor symptoms. Over time, the progressive nature of the disease increases the risk of complications such as falls and loss of independence, having a profound impact on quality of life. The complexity and heterogeneity of symptoms therefore warrant a holistic, multidisciplinary approach. Specific healthcare professionals, e.g. the movement disorders neurologist and the PD nurse specialist, are considered essential members of this multidisciplinary team. However, with our increasing knowledge about different aspects of the disease, other disciplines are also being recognized as important contributors to the healthcare team. Areas covered: The authors describe a selection of these relatively newly-recognized disciplines, including the specialist in vascular medicine, gastroenterologist, pulmonologist, neuro-ophthalmologist, urologist, geriatrician/elderly care physician, palliative care specialist and the dentist. Furthermore, they share the view of a person with PD on how patients and caregivers should be involved in the multidisciplinary team. Finally, they have included a perspective on the new role of the movement disorder neurologist, with care delivery via “tele-neurology”. Expert commentary: Increased awareness about the potential role of these ‘new’ professionals will further improve disease management and quality of life of PD patients.
Neurological disorders are now the leading source of disability globally, and the fastest growing neurological disorder in the world is Parkinson disease. From 1990 to 2015, the number of people with Parkinson disease doubled to over 6 million. Driven principally by aging, this number is projected to double again to over 12 million by 2040. Additional factors, including increasing longevity, declining smoking rates, and increasing industrialization, could raise the burden to over 17 million. For most of human history, Parkinson has been a rare disorder. However, demography and the by-products of industrialization have now created a Parkinson pandemic that will require heightened activism, focused planning, and novel approaches.
Current best medical treatment for patients with Parkinson's disease (PD) involves a medical professional who applies state-of-the-art knowledge of diagnostics and treatment-as derived from cohort studies and clinical trials-to the healthcare process of individual patients. Thus, the much-needed personalization of medicine depends on the abilities, experience and intuition of medical professionals to adjust group-based knowledge to individual decision making.Within 20 years from now, such personal clinical decisions will be largely supported by digital means, also defining a new ecosystem of healthcare often referred to as "digital medicine".We expect that the next phase of digitalization will include new"digital health pathways": Data-driven personalized decision support that is based on a combination of multimodal data sources, including evidence-based medical knowledge (e.g., clinical guidelines), personal disease profiles (including genetic determinants of disease progression and treatment response), insights into individual disease trajectories (thereby defining subgroups of patients) and individual patients' needs. Here, we illustrate the potential of this development by sketching the contours of a digitally supported care pathway for gait disability and falls. Such digital health pathways will support the introduction of personalized medicine for PD patients, allowing patients to benefit optimally from individually tailored treatments. This should result in a better quality of life for patients and lower costs for society.
Gait festination is one of the most characteristic gait disturbances in patients with Parkinson’s disease or atypical parkinsonism. Although festination is common and disabling, it has received little attention in the literature, and different definitions exist. Here, we argue that there are actually two phenotypes of festination. The first phenotype entails a primary locomotion disturbance, due to the so-called sequence effect: a progressive shortening of step length, accompanied by a compensatory increase in cadence. This phenotype strongly relates to freezing of gait with alternating trembling of the leg. The second phenotype results from a postural control problem (forward leaning of the trunk) combined with a balance control deficit (inappropriately small balance-correcting steps). In this viewpoint, we elaborate on the possible pathophysiological substrate of these two phenotypes of festination and discuss their management in daily clinical practice. Electronic supplementary material The online version of this article (10.1007/s00415-018-9146-7) contains supplementary material, which is available to authorized users.
Passive and non-obtrusive health monitoring using wearables can potentially bring new insights into the user's health status throughout the day and may support clinical diagnosis and treatment. However, identifying segments of free-living data that sufficiently reflect the user's health is challenging. In this work we have studied the problem of modelling real-life gait which is a very indicative behaviour for multiple movement disorders including Parkinson's disease (PD). We have developed a probabilistic framework for unsupervised analysis of the gait, clustering it into different types, which can be used to evaluate gait abnormalities occurring in daily life. Using a unique dataset which contains sensor and video recordings of people with and without PD in their own living environment, we show that our model driven approach achieves high accuracy gait detection and can capture clinical improvement after medication intake.
Background: Differentiation of Parkinson's disease (PD) from the various types of atypical parkinsonism (AP) such as multiple system atrophy (MSA), progressive supranuclear palsy (PSP), dementia with Lewy bodies (DLB), corticobasal syndrome (CBS) and vascular parkinsonism (VP), can be challenging, especially early in the disease course when symptoms overlap. A major unmet need in the diagnostic workup of these disorders is a diagnostic tool that differentiates the various disorders, preferably in the earliest disease stages when the clinical presentation is similar. Many diagnostic tests have been evaluated, but their added value was studied mostly in retrospective case-control studies that included patients with a straightforward clinical diagnosis. Here, we describe the design of a prospective cohort study in patients with parkinsonism in an early disease stage who have an uncertain clinical diagnosis. Our aim is to evaluate the diagnostic accuracy of (1) detailed clinical examination by a movement disorder specialist, (2) magnetic resonance imaging (MRI) techniques and (3) cerebrospinal fluid (CSF) biomarkers. Methods/design: Patients with parkinsonism with an uncertain clinical diagnosis and a disease course less than three years will be recruited. Patients will undergo extensive neurological examination, brain MRI including conventional and advanced sequences, and a lumbar puncture. The diagnosis (including level of certainty) will be defined by a movement disorders expert, neuroradiologist and neurochemist based on clinical data, MRI results and CSF results, respectively. The clinical diagnosis after three years' follow-up will serve as the "gold standard" reference diagnosis, based on consensus criteria and as established by two movement disorder specialists (blinded to the test results). Diagnostic accuracy of individual instruments and added value of brain MRI and CSF analysis after evaluation by a movement disorder expert will be calculated, expressed as the change in percentage of individuals that are correctly diagnosed with PD or AP. Discussion: This study will yield new insights into the diagnostic value of clinical evaluation by a movement disorder specialist, brain MRI and CSF analysis in discriminating PD from AP in early disease stages. The outcome has the potential to help clinicians in choosing the optimal diagnostic strategy for patients with an uncertain clinical diagnosis. Trial registration: NCT01249768, registered November 26 2010.
Background Parkinson’s disease (PD) is a chronic progressive disorder leading to increasing disability. While the symptoms and needs of patients in the early stages of their disease are well characterized, little information is available on patients in the late stage of the disease. Methods/design The Care of Late-Stage Parkinsonism (CLaSP) study is a longitudinal, multicenter, prospective cohort study to assess the needs and provision of care for patients with late stage Parkinsonism and their carers in six European countries (UK, France, Germany, Netherlands, Portugal, Sweden). In addition, it will compare the effectiveness of different health and social care systems. Patients with Parkinsonism with Hoehn and Yahr stage ≥IV in the “On”-state or Schwab and England stage 50% or less are evaluated at baseline and three follow-up time-points. Standardised questionnaires and tests are applied for detailed clinical, neuropsychological, behavioural and health-economic assessments. A qualitative study explores the health care needs and experiences of patients and carers, and an interventional sub-study evaluates the impact of specialist recommendations on their outcomes. Discussion Through the combined assessment of a range of quantitative measures and qualitative assessments of patients with late stage parkinsonism, this study will provide for the first time comprehensive and in-depth information on the clinical presentation, needs and health care provision in this population in Europe, and lay the foundation for improved outcomes in these patients. Trial registration The protocol was registered at ClinicalTrials.gov as NCT02333175 on 07/01/2015.
Data S1. Full distribution of occupational categories by Parkinson's disease status in the Rotterdam and Radboud Studies. Data S2. Detailed employment status of individuals with artistic or conventional occupations in the Rotterdam Study. Data S3. Examples and characteristics of occupations in each RIASEC category.
We report the first videotaped case of focal and task-specific dystonia of the upper limb that occurred exclusively while using a cue during billiard playing. The repetitive movements in conjunction with a highly skilled performance likely contributed to the development of this focal dystonia.
Parkinson’s disease (PD) is the second most common neurodegenerative disorder in elderly people. Currently, the diagnosis of PD is based on neurological examination, neuroimaging, and the response to dopaminergic medication. The diagnosis can be challenging, especially at early disease stages, when the symptoms of patients with atypical parkinsonism (APD) may strongly overlap. Therefore, reliable biomarkers that are able to identify patients with PD are much needed. Here, we aimed to identify and validate new biomarkers for PD in cerebrospinal fluid (CSF). We performed a profiling experiment using mass spectrometry (MS) of CSF from ten PD patients and ten matched non-neurological controls. We selected one protein, galectin-1 (Gal-1), which was differentially expressed in PD vs. controls, and quantified its concentrations in CSF by enzyme-linked immunosorbent assay (ELISA) in three new cohorts of 37 PD patients, 21 APD patients, and 44 controls. CSF levels of Gal-1 were lower in PD in both the discovery and validation experiments and discriminated PD from controls with moderate–high accuracy levels (ELISA: area under the curve = 0.7). Similar levels of Gal-1 were found in PD and APD. Gal-1 levels were correlated to age in all groups and correlated in the PD patients to CSF levels of total tau, phosphorylated tau, neurofilament light chain (NFL), and the mini-mental state examination (MMSE) score. We conclude that MS profiling of proteins may be a useful tool to identify novel biomarkers of neurological diseases and that CSF Gal-1 levels may discriminate PD from non-neurological controls.
- Nov 2018
A professional violinist reported increasing difficulties playing the violin. He executed the initial half of the musical piece well, but produced an increasing number of mistakes during the second half. Neurological examination was remarkable for bradykinesia and tremor. Formal acoustic analysis of finger taps and pronation‐supination showed a decrement in sound intensity and number of taps over time. Oscillations in performance correlated with a parkinsonian tremor. We interpret these findings as the audible equivalent of bradykinesia and tremor. Listening to bradykinesia and quantifying its decrement using acoustic analysis may offer a simple, objective and reliable supplement to the neurological examination. This article is protected by copyright. All rights reserved.
Background and objectives: To improve the care for patients with chronic neurological conditions like Parkinson's disease, identifying the core needs of patients is crucial. In this article, we present the Voice of the Customer approach (originally developed in the field of industry to probe the clients' needs), a novel methodology to identify these needs. Methods: A group of 12 discussants carried out in depth interviews to patients (n = 20), relatives (n = 12) and healthcare professionals (n = 11). The interviewers combined the most informative quotations into a comprehensive video, which was used as feedback to the interviewees. The interviewees then identified the most important needs in a consensus meeting. Results and conclusions: The approach revealed that patients were more concerned about the impact of Parkinson's disease on their daily lives than about the bio-medical aspects of the disease. Their top unmet needs were: (1) more self management; (2) better interdisciplinary collaboration between different healthcare professionals; (3) more time to discuss the future and possible scenarios; and (4) a healthcare professional acting as a single point of access, acting as personal case manager, either to solve problems directly or to direct patients to the professional best equipped to address the problem at hand. These results can now be used to further optimize the care for patients with Parkinson's disease.
- Sep 2018
UNSTRUCTURED Background: Cognitive decline is an important non-motor symptom in Parkinson’s disease (PD). Unfortunately, very few treatment options are available. Recent work pointed to small positive effects of non-pharmacological cognitive training in PD. Most of these trainings are solely computerized versions of paper-pencil cognitive trainings, lacking rewarding gamification stimulants that could help to promote adherence. Cases: Here, we present three PD patients with different ages, different disease stages and from various backgrounds, who all used a self-invented cognitive training that all included elements of personalization and gamification. Discussion: This emphasizes the large unmet need in this area. Researchers, health professionals and patients should now work together to develop structured and targeted cognitive training programs in PD.
Cognitive decline is an important nonmotor symptom in Parkinson disease (PD). Unfortunately, very few treatment options are available. Recent research pointed to small positive effects of nonpharmacological cognitive training in PD. Most of these trainings are performed under supervision and solely computerized versions of (traditional) paper-pencil cognitive training programs, lacking rewarding gamification stimulants that could help to promote adherence. By describing 3 different self-invented ways of cognitive gaming in patients with PD, we aimed to raise awareness for the potential of gamified cognitive training in PD patients. In addition, we hoped to inspire the readers with our case descriptions, highlighting the importance of both personalization and cocreation in the development of games for health. In this viewpoint, we have presented 3 PD patients with different ages, with different disease stages, and from various backgrounds, who all used self-invented cognitive training, including elements of personalization and gamification. To indicate generalization into a larger PD population, the recruitment results from a recent cognitive game trial are added. The presented cases show similarities in terms of awareness of their cognitive decline and the ways this process could potentially be counteracted, by looking for tools to train their cognition. On the basis of the response of the recruitment procedure, there seems to be interest in gamified cognitive training in a larger PD population too. Gamification may add to traditional therapies in terms of personalization and adherence. Positive results have already been found with gamified trainings in other populations, and the cases described here suggest that PD is also an attractive area to develop and test gamified cognitive trainings. However, no results of gamified cognitive trainings in PD have been published to date. This suggests an unmet need in this area and may justify the development of gamified cognitive training and its evaluation, for which our considerations can be used.
The evidence for physiotherapy is growing, showing a positive impact on functional activities involving gait, transfers and balance. Specific recommendations for physiotherapist, physicians and people with Parkinson's disease were published in the European Physiotherapy Guideline for Parkinson's disease. Here, we summarize the referral criteria, highlight the importance of accurate referral to specialized physiotherapists, and emphasize the potential benefits of expert care. As such, this paper offers very practical guidance for clinicians working with Parkinson's disease patients and who consider physiotherapy treatments for their patients.
Recent epidemiological observations have drawn attention to the rapid rise in the burden caused by Parkinson's disease over the past years, emphasizing that Parkinson's disease is a matter of serious concern for our future generations. A recent report by Public Health England corroborates this message, by providing new insight on trends in deaths associated with neurological diseases in England between 2001 to 2014. The report indicates that mortality associated with Parkinson's disease and related disorders increased substantially between 2001 and 2014. This trend is partially explained by increased longevity in the population. However, it is possible that changes in exposure to risk factors, recent improvements in multidisciplinary care (leading to prolonged survival), and improved diagnostic awareness or improved registration also influenced the observed trend. Furthermore, patients with Parkinson's disease and related disorders were found to die at an advanced age, and the majority die in a care home or hospital, despite a preponderant preference for many patients and their families to spend their last days at home. To combat these concerning observations, future efforts should be focused on providing resources for vulnerable elderly Parkinson patients, avoiding unplanned hospital admissions and out-of-home deaths as much as possible. Possible solutions include a community-based network of specifically trained allied health therapists, personal case managers for Parkinson patients, dedicated Parkinson nursing homes, and improved centralised support services from university clinics to regional community hospitals aimed at facilitating optimal wide-scale care delivery.
Het signaleren en interpreteren van een afwijkend looppatroon zijn belangrijk voor zowel de diagnostiek als de behandeling van de onderliggende aandoening. Omdat een verandering in het looppatroon bij veel aandoeningen al in de vroege fase klinisch waarneembaar is, kan herkenning hiervan helpen bij het tijdig stellen van de diagnose. In de medische opleiding wordt gebruikgemaakt van veelomvattende beschrijvingen van loopstoornissen, die alle mogelijke kenmerken van een klassiek syndroom opsommen. Maar patiënten melden zich zelden voor het eerst in de spreekkamer met álle klinische verschijnselen van een bepaalde ziekte, zeker niet in de vroegste fase. Juist in het begin vertonen patiënten vaak slechts één of hooguit enkele afwijkende loopkenmerken. Elk van deze individuele kenmerken is niet specifiek voor een bepaald ziektebeeld, maar kan gezien worden bij meerdere aandoeningen. We hebben daarom een praktische diagnostische benadering ontwikkeld, waarmee men een differentiële diagnose kan opstellen voor elk afwijkend kenmerk van het lopen. Door een gerichte anamnese en lichamelijk onderzoek kan vervolgens de juiste diagnose worden gesteld of kan de patiënt worden verwezen voor nadere diagnostiek.
Postural instability and freezing of gait (FoG) are key features of Parkinson's disease (PD) closely related to falls. Growing evidence suggests that co-existing postural deficits could influence the occurrence and severity of FoG. To date, the exact nature of this interrelationship remains largely unknown. We analyzed the complex interaction between postural instability and gait disturbance by comparing the findings available in the posturographic literature between patients with and without FoG. Results showed that FoG and postural instability are intertwined, can influence each other behaviorally and may coincide neurologically. The most common FoG-related postural deficits included weight-shifting impairments, and inadequate scaling and timing of postural responses most apparent at forthcoming postural changes under time constraints. Most likely, a negative cycle of combined and more severe postural deficits in people with FoG will enhance postural stability breakdown. As such, the wide brain network deficiencies involved in FoG may also concurrently influence postural stability. Future work needs to examine whether training interventions targeting both symptoms will have extra clinical benefits on fall frequency.
Background: In 2015, the International Parkinson and Movement Disorder Society published clinical diagnostic criteria for Parkinson's disease (PD). Although recent validation studies suggest high accuracy, one unmet need is for highly specific criteria for clinical trials in early/de novo PD. Objectives: The objective of this study was to generate and test a PD diagnostic criteria termed “clinically established early PD.” Methods: We modified the Movement Disorder Society criteria to increase specificity for early PD by removing all disease duration components and changing red flags to absolute exclusions. We then estimated the sensitivity/specificity of clinically established early PD criteria in patients with disease duration <5 years, selected from a 626‐patient validation study. Results: After documentation of parkinsonism, 18 individual exclusion criteria are assessed that preclude the diagnosis of “clinically established early PD.” Among 212 PD and 152 non‐PD patients, the estimated specificity was 95.4%, with 69.8% sensitivity. Conclusions: We describe high‐specificity criteria for de novo PD, which are freely available for use in clinical trials. © 2018 International Parkinson and Movement Disorder Society
Identification and interpretation of abnormal walking patterns is important, for the diagnosis as well as the treatment of the underlying condition. Since walking pattern changes can often be clinically observed at an early stage, their identification can help with timely diagnosis. Clinical training makes use of comprehensive descriptions of walking abnormalities that list all possible characteristics of a classic syndrome. However, patients rarely present at the office with all clinical symptoms of a specific disease, certainly not in the earliest stages. Especially in the beginning, patients often display only one or at best a few abnormal walking characteristics. None of these individual characteristics is specific for a certain disease, but may instead be seen in combination with several different disorders. For this reason, we have developed a practical diagnostic approach which allows making a differential diagnosis for each abnormal walking characteristic. Focused history taking and physical examination can then be used to make an accurate diagnose or to refer the patient for further diagnostics.
Background Creativity in Parkinson Disease (PD) is strongly related to dopaminergic activity and medication. We hypothesized that PD patients, including those who are in the prediagnostic phase of PD, are prone to choose highly‐structured ‘conventional’ professional occupations and avoid highly‐creative ‘artistic’ occupations. Methods At baseline of the population‐based Rotterdam Study, we asked 12,147 individuals aged >45 years about their latest occupation, and categorized occupations according to the RIASEC model. Participants underwent baseline and follow‐up (median 11 years) examinations for PD. We determined associations of artistic (versus any other occupation) and conventional (versus any other occupation) occupations with PD. Additionally, we pooled our results with a recently published case‐control study (‘Radboud Study’). Results At baseline, conventional occupations were common (n=4356 [36%]), while artistic occupations were rare (n=137 [1%]). There were 217 PD patients, including 91 prevalent and 126 incident PD patients. The risk of PD varied substantially across occupational categories (chi‐square=14.61; p=0.01). The penalized odds ratio (OR) of artistic occupations for PD was 0.19 (95% confidence interval [0.00;1.31]; p=0.11), while the OR of conventional occupations for PD was 1.23 ([0.95;1.66]; p=0.10). The direction and magnitude of ORs were similar in cross‐sectional and longitudinal subsamples. Pooled ORs across the Rotterdam and Radboud studies were 0.20 ([0.08;0.52]; p<0.001) for artistic and 1.23 ([0.92;1.67]; p=0.08) for conventional occupations. Conclusions The risk of PD varies substantially by choice of professional occupation. Our findings suggest that dopaminergic degeneration affects choice of occupation, which may already start in the prediagnostic phase of PD. This article is protected by copyright. All rights reserved.
Introduction: Outcome-based payment models (OBPMs) might solve the shortcomings of fee-for-service or diagnostic-related group (DRG) models using financial incentives based on outcome indicators of the provided care. This review provides an analysis of the characteristics and effectiveness of OBPMs, to determine which models lead to favourable effects. Methods: We first developed a definition for OBPMs. Next, we searched four data sources to identify the models: (1) scientific literature databases; (2) websites of relevant governmental and scientific agencies; (3) the reference lists of included articles; (4) experts in the field. We only selected studies that examined the impact of the payment model on quality and/or costs. A narrative evidence synthesis was used to link specific design features to effects on quality of care or healthcare costs. Results: We included 88 articles, describing 12 OBPMs. We identified two groups of models based on differences in design features: narrow OBPMs (financial incentives based on quality indicators) and broad OBPMs (combination of global budgets, risk sharing, and financial incentives based on quality indicators). Most (5 out of 9) of the narrow OBPMs showed positive effects on quality; the others had mixed (2) or negative (2) effects. The effects of narrow OBPMs on healthcare utilization or costs, however, were unfavourable (3) or unknown (6). All broad OBPMs (3) showed positive effects on quality of care, while reducing healthcare cost growth. Discussion: Although strong empirical evidence on the effects of OBPMs on healthcare quality, utilization, and costs is limited, our findings suggest that broad OBPMs may be preferred over narrow OBPMs.
Background In advanced stages of Parkinson’s disease (PD), patients and neurologists regularly face complex treatment decisions. Shared decision-making (SDM) can support the process where evidence, the clinician’s expertise and the patient’s preferences jointly contribute to reach an optimal decision. Here, we describe the rationale of our feasibility study protocol. The aim of the study is to test the feasibility of the SDM intervention by (1) analysing the acceptability of the intervention by users (i.e. professionals and patients), (2) assessing the level of implementation, (3) testing efficacy on a small scale and (4) evaluating the study procedures. Methods Using an uncontrolled before-after mixed methods design, patients in the pre-intervention group will receive information and decisional support as usual. Patients in the post-intervention group will receive the SDM intervention, consisting of an Option Grid™ patient decision aid and a website with supplementary information plus a value clarification tool for both patients and professionals. An Option Grid is a one-page, evidence-based summary of available options, listing the frequently asked questions that patients consider when making treatment decisions. A value clarification tool helps patients identify which option he/she prefers based on attributes in the treatment decision context. Neurologists and PD nurse specialists will receive a 1-h instruction on SDM and how to use the SDM intervention. Through purposive sampling, neurologists and PD nurse specialists will be recruited from both specialised neurology clinics and community-based hospitals. Included professionals will invite consecutive patients who are eligible for the advanced therapies. Data will be collected using questionnaires, interviews and audio observations of the consultations and by tracking users’ logging behaviour of the website. Data will be analysed using a mixed methods design. Discussion The mixed methods design will create a deeper understanding of how the SDM intervention affects the interactions between professionals (a neurologist and/or a PD nurse specialist) and the patient, when an advanced treatment is chosen. The results of the study will inform the design of an RCT to test the effectiveness of the SDM intervention. Trial registration NTR6649, retrospectively registered 28 August 2017.
Disturbances in reward processing occur in Parkinson's disease (PD) however it is unclear whether these are solely drug-related. We applied an event-related fMRI gambling task to a group of non-manifesting carriers (NMC) of the G2019S mutation in the LRRK2 gene, in order to assess the reward network in an "at risk" population for future development of PD. Sixty-eight non-manifesting participants, 32 of which were non-manifesting non-carriers (NMNC), performed a gambling task which included defined intervals of anticipation and response to both reward and punishment in an fMRI setup. Behavior and cerebral activations were measured using both hypothesis driven and whole brain analysis. NMC demonstrated higher trait anxiety scores (p = 0.04) compared to NMNC. Lower activations were detected among NMC during risky anticipation in the left nucleus accumbens (NAcc) (p = 0.05) and during response to punishment in the right insula (p = 0.02), with higher activations among NMC during safe anticipation in the right insula (p = 0.02). Psycho-Physiological Interaction (PPI) analysis from the NAcc and insula revealed differential connectivity patterns. Whole brain analysis demonstrated divergent between-group activations in distributed cortical regions, bilateral caudate, left midbrain, when participants were required to press the response button upon making their next chosen move. Abnormal neural activity in both the reward and motor networks were detected in NMC indicating involvement of the ventral striatum regardless of medication use in "at risk" individuals for future development of PD.
Deep brain stimulation effectively relieves most motor symptoms of Parkinson's disease • Effects on freezing of gait remain controversial with reports of improvement, worsening, and even induction post-surgery. Our objective was to evaluate the effects of bilateral subthalamic nucleus deep brain stimulation on subjective and objective freezing of gait, with a special focus on freezing of gait subtypes and patterns.
Question - What would be a good reference in a leading journal that criticizes the value of traditional RCTs?
many thanks Martha, and apologies for the late response - I do not use research gate much, and had forgotten all about my question. Much appreciated though. Bas
Objective: Differentiating Parkinson's disease (PD) from atypical parkinsonian disorders (APD) such as Multiple System Atrophy, parkinsonian type (MSA-p) or Progressive Supranuclear Palsy (PSP-RS) can be challenging. Early signs of postural Instability and gait disability (PIGD) are considered clues that may signal presence of APD. However, it remains unknown which PIGD test - or combination of tests - can best distinguish PD from APD. We evaluated the discriminative value of several widely-used PIGD tests, and aimed to develop a short PIGD evaluation that can discriminate parkinsonian disorders. Methods: In this multicentre cohort study patients were recruited by 11 European MSA Study sites. Patients were diagnosed using standardized criteria. Postural instability and gait disability was evaluated using interviews and several clinical tests. Results: Nineteen PD, 21 MSA-p and 25 PSP-RS patients were recruited. PIGD was more common in APD compared to PD. There was no significant difference in axial symptoms between PSP-RS and MSA-p, except for self-reported falls (more frequent in PSP-RS patients). The test with the greatest discriminative power to distinguish APD from PD was the ability to perform tandem gait (AUC 0.83; 95% CI 71-94; p < 0.001), followed by the retropulsion test (AUC 0.8; 95% CI 0.69-0.91; p < 0.001) and timed-up-and-go test (TUG) (AUC 0.77; 95% CI 0.64-0.9; p = 0.001). The combination of these three tests yielded highest diagnostic accuracy (AUC 0.96; 95% CI 0.92-1.0; p < 0.001). Conclusions: Our study suggests that simple "bedside" PIGD tests - particularly the combination of tandem gait performance, TUG and retropulsion test - can discriminate APD from PD.
- Jun 2018
Background: We undertook this study to identify patients with Parkinson disease (PD) with no or rare falls who may progress to frequent falling by their next annual follow-up visit. Methods: We analyzed data in the National Parkinson Foundation Quality Improvement Initiative database to identify factors predicting which patients with PD with no or rare falls at the baseline visit will report at least monthly falls at the annual follow-up visit. Multivariable models were constructed using logistic regression. Variables were introduced in 4 blocks: in the 1st block, variables present at or before the baseline visit were entered; in the 2nd, baseline visit assessments; in the 3rd, interventions implemented during baseline visit; and, in the 4th block, changes in comorbidities, living situation, and treatment between visits. Results: Of 3,795 eligible participants, 3,276 (86.3%) reported no or rare falls at baseline visit, and of them, 382 (11.7%) reported at least monthly falls at follow-up visit. Predictors included female sex, <90% diagnostic certainty, motor fluctuations, levodopa treatment, antidepressant treatment, prior deep brain stimulation (DBS), worse quality of life, Hoehn & Yahr stage 2 or 3, worse semantic fluency, and, between visits, addition of amantadine, referral to occupational therapy, social services, or DBS, new diagnoses of cancer or osteoarthritis, and increased emergency visits. Conclusions: This large-scale analysis identified several predictors of progression to falling in PD. Such identifiers may help target patient subgroups for falls prevention intervention. Some factors are modifiable, offering opportunities for developing such interventions.
- May 2018
Introduction: Camptocormia is defined as an involuntary, marked flexion of the thoracolumbar spine appearing during standing or walking and resolving in the supine position or when leaning against a wall. However, there is no established agreement on the minimum degree of forward flexion needed to diagnose camptocormia. Likewise, the current definition does not categorize camptocormia on the basis of the bending fulcrum. Methods: We performed a survey among movement disorders experts to identify camptocormia using images of patients with variable degrees and types of forward trunk flexion by fulcrum (upper and lower fulcra). We tested the subsequently generated diagnostic criteria in a sample of 131 consecutive patients referred for evaluation of postural abnormalities. Results: Experts reached full consensus on lower camptocormia (L1-Sacrum, hip flexion) with a bending angle ≥30° and upper camptocormia (C7 to T12-L1) with a bending angle ≥45°. This definition detected camptocormia in 9/131 consecutive PD patients (2 upper/7 lower) but excluded camptocormia in 71 patients considered to have camptocormia by the referring neurologist. Conclusions: Camptocormia can be defined as "an involuntary flexion of the spine appearing during standing or walking and resolving in the supine position of at least 30° at the lumbar fulcrum (L1-Sacrum, hip flexion, i.e. lower camptocormia) and/or at least 45° at the thoracic fulcrum (C7 to T12-L1, i.e. upper camptocormia)". Strict criteria for camptocormia are met by 7% of patients with abnormal posture. The ascertainment of upper and lower camptocormia subtypes could improve the validity of epidemiological studies and assist future therapeutic trials.
Introduction: The DUALITY trial recently showed that both integrated and consecutive dual-task training improve dual-task gait velocity, without increasing fall risks in patients with Parkinson's disease (PD). Gait velocity was the primary outcome; not reported, however, were important gait measures related to the risk of falling such as gait variability. In this secondary analysis, we compared the efficacy of the two training programs with respect to spatiotemporal outcome parameters. Methods: 121 PD patients (Hoehn and Yahr stage II-III while ON medication) were randomly assigned to either a consecutive group (n = 65) in which cognitive and gait tasks were trained separately, or an integrated group (n = 56) in which cognitive and gait tasks were trained simultaneously. Both groups received 24 in-home physiotherapy sessions for six consecutive weeks. Two baseline measurements were performed during a six-week control period prior to the interventions. Gait was evaluated under three different (and untrained) dual-task conditions immediately after the treatment period and at 12-week follow-up. Results: Both training modalities had a comparable effect on spatiotemporal gait parameters. A significant post-training increase in stride length (P < .001) and cadence (P < .001) was found under both the single and the dual-task conditions. These improvements were maintained at follow-up, although the effect was slightly reduced. No significant changes were found for gait variability under single and dual-task conditions. Conclusion: We found both integrated and consecutive dual-task training to be safe and effective in improving several spatiotemporal gait parameters under trained and untrained dual-task conditions.
The use of wearable sensing technology for objective, non-invasive and remote clinimetric testing of symptoms has considerable potential. However, the accuracy achievable with such technology is highly reliant on separating the useful from irrelevant sensor data. Monitoring patient symptoms using digital sensors outside of controlled, clinical lab settings creates a variety of practical challenges, such as recording unexpected user behaviors. These behaviors often violate the assumptions of clinimetric testing protocols, where these protocols are designed to probe for specific symptoms. Such violations are frequent outside the lab and affect the accuracy of the subsequent data analysis and scientific conclusions. To address these problems, we report on a unified algorithmic framework for automated sensor data quality control, which can identify those parts of the sensor data that are sufficiently reliable for further analysis. Combining both parametric and nonparametric signal processing and machine learning techniques, we demonstrate that across 100 subjects and 300 clinimetric tests from three different types of behavioral clinimetric protocols, the system shows an average segmentation accuracy of around 90%. By extracting reliable sensor data, it is possible to strip the data of confounding factors in the environment that may threaten reproducibility and replicability.
Background: Chronically ill patients have to cope with transfers in the level or setting of care. Patients with prevalent disorders such as diabetes mellitus can be supported by their general practitioner (GP) when experiencing such care changes, as the GP already offers them disease-specific care. For community-dwelling patients with low-prevalent diseases such as Parkinson’s disease (PD) – for which disease-specific care is provided by medical specialists – tailoring support to handle care changes requires more insight into patients’ coping. Objectives: To explore PD patients’ coping with care changes. Methods: A qualitative interview study was performed in 2013–2015 with a purposive sample of 16 community-dwelling PD patients in the Netherlands. A research assistant visited patients every month to explore if they had experienced a care change. If so, patients were interviewed face-to-face. An inductive approach to comparative content analysis was used. Results: Patients encountered a variety of care changes such as changes in the level of unpaid care, the purchase of tools, modification of pharmacotherapy or admission to hospital. Being able to anticipate, initiate and independently handle care changes contributes to patients’ sense of control and acceptance of the post-change situation. Patients, who commenced care changes themselves, had more realistic expectations of it. Conclusion: Community-dwelling PD patients seem to be able to cope with the care changes they face. Offering education to facilitate their anticipation and initiation of changes in care and their ability to act independently, can contribute to patients’ wellbeing. GPs can play a role in this.
Background: Telemedicine is increasingly used to care for patients with movement disorders, but data regarding its global use are limited. Introduction: To obtain baseline international data about telemedicine use among movement disorder clinicians. Methods: An online survey was sent to all 6,056 Movement Disorder Society members in 2015. Scope, reimbursement, and perceived quality of telemedicine were assessed. Results: There were 549 respondents (9.1% overall response rate) from 83 countries. Most (85.8%) were physicians, and most (70.9%) worked in an academic or university practice. Half of respondents (n = 287, from 57 countries) used telemedicine for clinical care; activities included e-mail (63.2%), video visits (follow-up [39.7%] and new [35.2%]), and video-based education (35.2%). One hundred five respondents personally conducted video visits, most frequently to outpatient clinics (53.5%), patient homes (30.8%), and hospital inpatients (30.3%). The most common challenges were a limited neurological examination (58.9%) and technological difficulties (53.3%), and the most common benefits were reduced travel time (92.9%) and patient costs (60.1%). The most frequent reimbursements were none (39.0%), public insurance (24.5%), and patient payment (9.3%). Half of respondents planned to use telemedicine in the future, and three-quarters were interested in telemedicine education. Conclusions: More than 250 respondents around the world engage in telemedicine for movement disorders; most perceived benefit for patients, despite challenges and reimbursement for clinicians. Formal instruction on telemedicine is highly desired. Although the survey response was low and possibly biased to over represent those with telemedicine experience, the study provides baseline data for future comparison and to improve telemedicine delivery.
Background: In a randomized control trial conducted in patients with Parkinson's disease, a treadmill training program combined with virtual reality that targeted motor and cognitive aspects of safe ambulation led to fewer falls, compared with treadmill training alone. Objective: To investigate if the 2 types of training differentially affected prefrontal activation and if this might explain differences in fall rates after the intervention. Methods: Sixty-four patients with Parkinson's disease were randomized into the treadmill training arm (n = 34, mean age 73.1 ± 1.1 years, 64% men, disease duration 9.7 ± 1.0 years) or treadmill training with virtual reality arm (n = 30, mean age 70.1 ± 1.3 years, 71% men, disease duration 8.9 ± 1.1 years). Prefrontal activation during usual, dual-task, and obstacle negotiation walking was assessed before and after 6 weeks of training, using a functional near-infrared spectroscopy system. Results: Treadmill training with and without virtual reality reduced prefrontal activation during walking ( P < .001), with specific interactions related to training arm ( P = .01), lateralization ( P = .05), and walking condition ( P = .001). For example, among the subjects who trained with treadmill training alone, prefrontal activation during dual-task walking and obstacle negotiation increased after training, while in the combined training arm, activation decreased. Conclusions: Prefrontal activation during usual and during more challenging walking conditions can be altered in response to 2 different types of training. The addition of a cognitive training component to a treadmill exercise program apparently modifies the effects of the training on the magnitude and lateralization of prefrontal activation and on falls, extending the understanding of the plasticity of the brain in PD.
Freezing of gait is a devastating symptom of Parkinson's disease and other forms of parkinsonism. It poses a major burden on both patients and their families, as freezing often leads to falls, fall-related injuries and a loss of independence. Treating freezing of gait is difficult for a variety of reasons: it has a paroxysmal and unpredictable nature; a multifaceted pathophysiology, with an interplay between motor elements (disturbed stepping mechanisms) and non-motor elements (cognitive decline, anxiety); and a complex (and likely heterogeneous) underlying neural substrate, involving multiple failing neural networks. In recent years, advances in translational neuroscience have offered new insights into the pathophysiology underlying freezing. Furthermore, the mechanisms behind the effectiveness of available treatments (or lack thereof) are better understood. Driven by these concepts, researchers and clinicians have begun to improve currently available treatment options, and develop new and better treatment methods. Here, we evaluate the range of pharmacological (i.e. closed-looped approaches), surgical (i.e. multi-target and adaptive deep brain and spinal cord stimulation) and behavioural (i.e. biofeedback and cueing on demand) treatment options that are under development, and propose novel avenues that are likely to play a crucial role in the clinical management of freezing of gait in the near future. The outcomes of this review suggest that the successful future management of freezing of gait will require individualized treatments that can be implemented in an on-demand manner in response to imminent freezing. With this review we hope to guide much-needed advances in treating this devastating symptom of Parkinson's disease.
Background: People with PD (PWP) have an increased risk of becoming inactive. Wearable sensors can provide insights into daily physical activity and walking patterns. Research questions: (1) Is the severity of motor fluctuations associated with sensor-derived average daily walking quantity? (2) Is the severity of motor fluctuations associated with the amount of change in sensor-derived walking quantity after levodopa intake? Methods: 304 Dutch PWP from the Parkinson@Home study were included. At baseline, all participants received a clinical examination. During the follow-up period (median: 97 days; 25-Interquartile range-IQR: 91 days, 75-IQR: 188 days), participants used the Fox Wearable Companion app and streamed smartwatch accelerometer data to a cloud platform. The first research question was assessed by linear regression on the sensor-derived mean time spent walking/day with the severity of fluctuations (MDS-UPDRS item 4.4) as independent variable, controlled for age and MDS-UPDRS part-III score. The second research question was assessed by linear regression on the sensor-derived mean post-levodopa walking quantity, with the sensor-derived mean pre-levodopa walking quantity and severity of fluctuations as independent variables, controlled for mean time spent walking per day, age and MDS-UPDRS part-III score. Results: PWP spent most time walking between 8am and 1pm, summing up to 72 ± 39 (mean ± standard deviation) minutes of walking/day. The severity of motor fluctuations did not influence the mean time spent walking (B = 2.4 ± 1.9, p = 0.20), but higher age (B = -1.3 ± 0.3, p = < 0.001) and greater severity of motor symptoms (B = -0.6 ± 0.2, p < 0.001) was associated with less time spent walking (F(3216) = 14.6, p < .001, R2 = .17). The severity of fluctuations was not associated with the amount of change in time spent walking in relation to levodopa intake in any part of the day. Significance: Analysis of sensor-derived gait quantity suggests that the severity of motor fluctuations is not associated with changes in real-life walking patterns in mildly to moderate affected PWP.
Objective: To disentangle the different forms of postural tremors in Parkinson disease (PD). Methods: In this combined observational and intervention study, we measured resting and postural tremor characteristics in 73 patients with tremulous PD by using EMG of forearm muscles. Patients were measured both "off" medication (overnight withdrawal) and after dispersible levodopa-benserazide 200/50 mg. We performed an automated 2-step cluster analysis on 3 postural tremor characteristics: the frequency difference with resting tremor, the degree of tremor suppression after posturing, and the dopamine response. Results: The cluster analysis revealed 2 distinct postural tremor phenotypes: 81% had re-emergent tremor (amplitude suppression, frequency difference with resting tremor 0.4 Hz, clear dopamine response) and 19% had pure postural tremor (no amplitude suppression, frequency difference with resting tremor 3.5 Hz, no dopamine response). This finding was manually validated (accuracy of 93%). Pure postural tremor was not associated with clinical signs of essential tremor or dystonia, and it was not influenced by weighing. Conclusion: There are 2 distinct postural tremor phenotypes in PD, which have a different pathophysiology and require different treatment. Re-emergent tremor is a continuation of resting tremor during stable posturing, and it has a dopaminergic basis. Pure postural tremor is a less common type of tremor that is inherent to PD, but has a largely nondopaminergic basis.
Background: Postural instability and freezing of gait (FOG) are major problems in patients with Parkinson's disease (PD), and both contribute to falls. However, the interrelationship between these 2 deficits is still unclear. Objective: This study investigated whether dual-tasking influenced postural control differently in freezers (FOG+) and nonfreezers (FOG-). Methods: Thirty-three patients with PD (19 FOG+, 14 FOG-, well-matched) and 28 healthy controls underwent 4 postural control tasks, consisting of standing on either stable or unstable surfaces with eyes open or closed. Each condition was performed with and without a cognitive dual-task (DT). Center of pressure and center of mass variables and cognitive DT performance outcomes were investigated. Results: Postural stability decreased to a larger extent in FOG+ under DT conditions compared with the other groups, although overall most differences were found between FOG+ and controls. FOG+ exhibited worse postural control compared with FOG- under stable surface DT conditions, shown by higher medial-lateral sway measures (group × surface × task, P < .05). Also, postural DT cost (%) was higher in FOG+ than in FOG- in unstable surface conditions without vision. Controls performed better on the cognitive DT when balancing compared with sitting, whereas this improvement was absent in both PD subgroups and more so in FOG+. Conclusions: Postural stability in FOG+ deteriorated more than in FOG- and controls upon cognitive load. Our results extend earlier findings on gait that the compensatory mechanisms to cope with DT stance are insufficient in FOG+. The findings highlight the need for adapted rehabilitation programs for this subgroup, comprising motor-cognitive balance training.
Neurological disorders of gait, balance and posture are both debilitating and common. Adequate recognition of these so-called disorders of axial mobility is important as they can offer useful clues to the underlying pathology in patients with an uncertain clinical diagnosis, such as those early in the course of neurological disorders. Medical teaching programmes typically take classic clinical presentations as the starting point and present students with a representative constellation of features that jointly characterize a particular axial motor syndrome. However, patients rarely present in this way to a physician in clinical practice. Particularly in the early stages of a disease, patients might display just one (or at best only a few) abnormal signs of gait, balance or posture. Importantly, these individual signs are never pathognomonic for any specific disorder but rather come with an associated differential diagnosis. In this Perspective, we offer a new diagnostic approach in which the presenting signs are taken as the starting point for a focused differential diagnosis and a tailored search into the underlying neurological syndrome.
Wearable devices can capture objective day-to-day data about Parkinson’s Disease (PD). This study aims to assess the feasibility of implementing wearable technology to collect data from multiple sensors during the daily lives of PD patients. The Parkinson@home study is an observational, two-cohort (North America, NAM; The Netherlands, NL) study. To recruit participants, different strategies were used between sites. Main enrolment criteria were self-reported diagnosis of PD, possession of a smartphone and age≥18 years. Participants used the Fox Wearable Companion app on a smartwatch and smartphone for a minimum of 6 weeks (NAM) or 13 weeks (NL). Sensor-derived measures estimated information about movement. Additionally, medication intake and symptoms were collected via self-reports in the app. A total of 953 participants were included (NL: 304, NAM: 649). Enrolment rate was 88% in the NL (n = 304) and 51% (n = 649) in NAM. Overall, 84% (n = 805) of participants contributed sensor data. Participants were compliant for 68% (16.3 hours/participant/day) of the study period in NL and for 62% (14.8 hours/participant/day) in NAM. Daily accelerometer data collection decreased 23% in the NL after 13 weeks, and 27% in NAM after 6 weeks. Data contribution was not affected by demographics, clinical characteristics or attitude towards technology, but was by the platform usability score in the NL (χ² (2) = 32.014, p<0.001), and self-reported depression in NAM (χ²(2) = 6.397, p = .04). The Parkinson@home study shows that it is feasible to collect objective data using multiple wearable sensors in PD during daily life in a large cohort.
Objective: To assess, in a cross-sectional study, the feasibility and immediate efficacy of laser shoes, a new ambulatory visual cueing device with practical applicability for use in daily life, on freezing of gait (FOG) and gait measures in Parkinson disease (PD). Methods: We tested 21 patients with PD and FOG, both "off" and "on" medication. In a controlled gait laboratory, we measured the number of FOG episodes and the percent time frozen occurring during a standardized walking protocol that included FOG provoking circumstances. Participants performed 10 trials with and 10 trials without cueing. FOG was assessed using offline video analysis by an independent rater. Gait measures were recorded in between FOG episodes with the use of accelerometry. Results: Cueing using laser shoes was associated with a significant reduction in the number of FOG episodes, both "off" (45.9%) and "on" (37.7%) medication. Moreover, laser shoes significantly reduced the percent time frozen by 56.5% (95% confidence interval [CI] 32.5-85.8; p = 0.004) when "off" medication. The reduction while "on" medication was slightly smaller (51.4%, 95% CI -41.8 to 91.5; p = 0.075). These effects were paralleled by patients' positive subjective experience on laser shoes' efficacy. There were no clinically meaningful changes in the gait measures. Conclusions: These findings demonstrate the immediate efficacy of laser shoes in a controlled gait laboratory, and offer a promising intervention with potential to deliver in-home cueing for patients with FOG. Classification of evidence: This study provides Class III evidence that for patients with PD, laser shoes significantly reduce FOG severity (both number and duration of FOG episodes).