BACKGROUND: Debilitating problems with hand function experienced by people with Parkinson\'s disease (PD) can worsen during multitasking.
OBJECTIVE: To investigate the effects of dual-task interference on a pegboard task in people with mild to moderately severe PD.
METHODS: Descriptive analysis.
METHODS: A secondary analysis of baseline data from the ParkinsonNet physiotherapy study conducted in 2006 in the Netherlands. The 9-hole peg test was performed with the more affected hand under single- and dual-task conditions. In dual-task trials, a cognitive task was added. The patient specific index-Parkinson\'s disease identified two functional priority groups-those reporting arm and hand problems as a priority for allied health management (\"upper extremity priority\") and those prioritizing other issues (\"other priority\"). We investigated differences in single- and dual-task performance at different levels of disease severity (Hoehn and Yahr stage) and for the two priority groups, and calculated the dual-task effect.
RESULTS: Participants were 566 people with PD (Hoehn and Yahr stages I-IV). Dual-task interference occurred at each disease stage. Significant interactions existed between the task condition and disease severity (F (3, 559) = 4.28, p = 0.005) and task condition and priority group (F (1, 561) = 4.44, p = 0.036). Dual-task interference was greater in participants with more advanced disease or those prioritizing upper extremity problems.
CONCLUSIONS: We described the effects of dual-task interference on more affected hand performance of a standardized dexterity test in a broad sample of people with PD. Dual-task interference may impact the daily lives of people with PD, especially those with more severe disease or who report arm and hand problems. It is important for clinicians to consider dual-task interference during upper extremity assessment and treatment.

OBJECTIVE: The objective of this study is to compare the differences in effective connectivity within the default mode network (DMN) subsystems between patients with Parkinson\'s disease with mild cognitive impairment (PD-MCI) and patients with Parkinson\'s disease with normal cognition (PD-CN). The mechanisms underlying DMN dysfunction in PD-MCI patients and its association with clinical cognitive function in PD-MCI are aimed to be investigated.
METHODS: The spectral dynamic causal model (spDCM) was employed to analyze the effective connectivity of functional magnetic resonance imaging (fMRI) data in the resting state for the DMN subsystems, which include the medial prefrontal cortex (MPFC), posterior cingulate cortex (PCC), left and right angular gyrus (LAG, RAG) in 23 PD-MCI and 22 PD-CN patients, respectively. The effective connectivity values of DMN subsystems in the two groups were statistically analyzed using a two-sample t-test. The Spearman correlation analysis was used to test the correlation between the effective connectivity values of the subsystems with significant differences between the two groups and the clinical cognitive function (as measured by Montreal Cognitive Assessment Scale (MoCA) score).
RESULTS: Statistical analysis revealed significant differences in the effective connections of MPFC-LAG and LAG-PCC between the two patient groups (MPFC-LAG: t = -2.993, p < 0.05; LAG-PCC: t = 2.174, p < 0.05).
CONCLUSIONS: The study findings suggest that abnormal strength and direction of effective connections between DMN subsystems are found in PD-MCI patients.

Parkinson\'s disease (PD) is a neurodegenerative disorder characterized by the progressive loss of dopaminergic neurons in the substantia nigra pars compacta region of the midbrain and the formation of intracellular protein aggregates known as Lewy bodies, of which a major component is the protein α-synuclein. Several studies have suggested that mitochondria play a central role in the pathogenesis of PD, encompassing both familial and sporadic forms of the disease. Mitochondrial dysfunction is attributed to bioenergetic impairment, increased oxidative stress, damage to mitochondrial DNA, and alteration in mitochondrial morphology. These alterations may contribute to improper functioning of the central nervous system and ultimately lead to neurodegeneration. The perturbation of mitochondrial function makes it a potential target, worthy of exploration for neuroprotective therapies and to improve mitochondrial health in PD. Thus, in the current review, we provide an update on mitochondria-based therapeutic approaches toward α-synucleinopathies in PD.

Deep brain stimulation (DBS) is a common therapy for managing Parkinson\'s disease (PD) in clinical practice. However, a complete understanding of its mode of action is still needed. DBS is believed to work primarily through electrical and neurochemical pathways. Furthermore, DBS has other mechanisms of action. This review explores the fundamental concepts and applications of DBS in treating PD, including its mechanisms, clinical implications, and recent research.

Parkinson\'s disease (PD) is a debilitating condition that affects 1.8% of people 65 years of age and older. Patients with PD often require hospitalization and are frequently admitted through the emergency department (ED). Notably, their hospital durations tend to be lengthier compared with patients without PD. The primary outcome of this research was to compare the length of stay (LOS) of patients who received carbidopa-levodopa (CL) in the ED with those who did not. Secondary outcomes included 30-day-readmission rates and administration of injectable for agitation. In addition, the percentage of patients receiving CL before and after an information management technology (IMT) alert implementation was compared in a sub-analysis. Patients that received CL during their inpatient stay were identified by a database report in this retrospective study. Patients were excluded if they were not admitted through the ED, younger than 65 years of age, or admitted to the intensive care unit after the ED. There was a total of 266 in the control group and 217 patients in the intervention group. The intervention group had a significantly shorter LOS than the control group (3.29 vs 5.37 days; P = 0.002), significantly less frequent 30-day readmissions (P = 0.032), and used fewer injectables for agitation (P = 0.035). The sub-analysis of the IMT alert revealed that prior to the alert\'s implementation, 28.5% of patients received CL in the ED; whereas post-alert, this percentage increased to 91.4% (P < 0.001). The results of this study found that the group of PD patients who received CL in the ED had shorter LOS, lower 30-day readmissions, and used less injectables for agitation compared with the group that did not receive CL in the ED. This improvement is possibly due to continuity of CL supply considering its short half-life and clinical importance for PD.

BACKGROUND: Parkinson\'s disease (PD) is a progressive neurodegenerative disorder characterized by motor and nonmotor system manifestations and psychiatric symptoms. The aim of this study was to estimate the age- and sex-specific incidence of PD in Germany using an illness-death model and a corresponding partial differential equation (PDE) based on prevalence and mortality data.
METHODS: Based on a PDE that describes the dynamics in an illness-death model, the age- and sex-specific incidence of PD in Germany was estimated using published prevalence and mortality rates. Prevalence rates were provided by the Central Institute for Statutory Health Insurance (Zi) for the period from 2010 to 2019. Parkinson\'s related mortality was estimated based on comparable population data from Norway. Bootstrapping was used for incidence estimation (median of 5000 samples) and to obtain 95% confidence intervals to interpret the accuracy of the incidence estimation.
RESULTS: Men had higher incidences of PD than women at all ages. The highest incidences (median of 5000 bootstrap samples) for both groups were estimated for the age of 85 years with an incidence of 538.49 per 100,000 person-years (py) in men and 284.09 per 100,000 py in women, with an increasing width of bootstrapping 95% CIs showing greater uncertainty in the estimation at older ages.
CONCLUSIONS: The illness-death model and the corresponding PDE, which describes changes in prevalence as a function of mortality and incidence, can be used to estimate the incidence of PD as a chronic disease. As overestimation of incidence is less likely with this method, we found incidence rates of Parkinson\'s disease that are suitable for further analyses with a lower risk of bias.

BACKGROUND: Genetic testing is essential to identify research participants for clinical trials enrolling people with Parkinson disease (PD) carrying a variant in the glucocerebrosidase (GBA) or leucine-rich repeat kinase 2 (LRRK2) genes. The limited availability of professionals trained in neurogenetics or genetic counseling is a major barrier to increased testing. Telehealth solutions to increase access to genetics education can help address issues around counselor availability and offer options to patients and family members.
OBJECTIVE: As an alternative to pretest genetic counseling, we developed a web-based genetics education tool focused on GBA and LRRK2 testing for PD called the Interactive Multimedia Approach to Genetic Counseling to Inform and Educate in Parkinson\'s Disease (IMAGINE-PD) and conducted user testing and usability testing. The objective was to conduct user and usability testing to obtain stakeholder feedback to improve IMAGINE-PD.
METHODS: Genetic counselors and PD and neurogenetics subject matter experts developed content for IMAGINE-PD specifically focused on GBA and LRRK2 genetic testing. Structured interviews were conducted with 11 movement disorder specialists and 13 patients with PD to evaluate the content of IMAGINE-PD in user testing and with 12 patients with PD to evaluate the usability of a high-fidelity prototype according to the US Department of Health and Human Services Research-Based Web Design & Usability Guidelines. Qualitative data analysis informed changes to create a final version of IMAGINE-PD.
RESULTS: Qualitative data were reviewed by 3 evaluators. Themes were identified from feedback data of movement disorder specialists and patients with PD in user testing in 3 areas: content such as the topics covered, function such as website navigation, and appearance such as pictures and colors. Similarly, qualitative analysis of usability testing feedback identified additional themes in these 3 areas. Key points of feedback were determined by consensus among reviewers considering the importance of the comment and the frequency of similar comments. Refinements were made to IMAGINE-PD based on consensus recommendations by evaluators within each theme at both user testing and usability testing phases to create a final version of IMAGINE-PD.
CONCLUSIONS: User testing for content review and usability testing have informed refinements to IMAGINE-PD to develop this focused, genetics education tool for GBA and LRRK2 testing. Comparison of this stakeholder-informed intervention to standard telegenetic counseling approaches is ongoing.

BACKGROUND: The management of neurodegenerative diseases (NDDs) in older populations is usually demanding and involves care provision by various health care services, resulting in a greater burden on health care systems in terms of costs and resources. The convergence of various health services within integrated health care models, which are enabled and adopted jointly with information and communication technologies (ICTs), has been identified as an effective alternative health care solution. However, its widespread implementation faces formidable challenges. Both the development and implementation of integrated ICTs are linked to the collaboration and acceptance of different groups of stakeholders beyond patients and health care professionals, with reported discrepancies in the needs and preferences among these groups.
OBJECTIVE: Complementing a previous publication, which reported on the needs and requirements of end users in the development of the European Union-funded project PROCare4Life (Personalized Integrated Care Promoting Quality of Life for Older People), this paper aimed to report on the opinions of other key stakeholders from various fields, including academia, media, market, and decision making, for improving the acceptability and implementation of an integrated ICT-based health care platform supporting the management of NDDs.
METHODS: The study included 30 individual semistructured interviews that took place between June and August 2020 in 5 European countries (Germany, Italy, Portugal, Romania, and Spain). Interviews were mostly conducted online, except in cases where participants requested to be interviewed in person. In these cases, COVID-19 PROCare4Life safety procedures were applied.
RESULTS: This study identified 2 themes and 5 subthemes. User engagement, providing training and education, and the role played by the media were identified as strategic measures to ensure the acceptability of ICT-based health care platforms. Sustainable funding and cooperation with authorities were foreseen as additional points to be considered in the implementation process.
CONCLUSIONS: The importance of the user-centered design approach in ensuring the involvement of users in the development of ICT-based platforms has been highlighted. The most common challenges that hinder the acceptability and implementation of ICT-based health care platforms can be addressed by creating synergies among the efforts of users, academic stakeholders, developers, policy makers, and decision makers. To support future projects in developing ICT-based health care platforms, this study outlined the following recommendations that can be integrated when conducting research on users\' needs: (1) properly identify the particular challenges faced by future user groups without neglecting their social and clinical contexts; (2) iteratively assess the digital skills of future users and their acceptance of the proposed platform; (3) align the functionalities of the ICT platform with the real needs of future users; and (4) involve key stakeholders to guide the reflection on how to implement the platform in the future.
UNASSIGNED: RR2-10.2196/22463.

OBJECTIVE: Parkinson disease (PD) is a common progressive neurodegenerative disorder in our ageing society. Early-stage PD biomarkers are desired for timely clinical intervention and understanding of pathophysiology. Since one of the characteristics of PD is the progressive loss of dopaminergic neurons in the substantia nigra pars compacta, we propose a feature extraction method for analysing the differences in the substantia nigra between PD and non-PD patients.
METHODS: We propose a feature-extraction method for volumetric images based on a rank-1 tensor decomposition. Furthermore, we apply a feature selection method that excludes common features between PD and non-PD. We collect neuromelanin images of 263 patients: 124 PD and 139 non-PD patients and divide them into training and testing datasets for experiments. We then experimentally evaluate the classification accuracy of the substantia nigra between PD and non-PD patients using the proposed feature extraction method and linear discriminant analysis.
RESULTS: The proposed method achieves a sensitivity of 0.72 and a specificity of 0.64 for our testing dataset of 66 non-PD and 42 PD patients. Furthermore, we visualise the important patterns in the substantia nigra by a linear combination of rank-1 tensors with selected features. The visualised patterns include the ventrolateral tier, where the severe loss of neurons can be observed in PD.
CONCLUSIONS: We develop a new feature-extraction method for the analysis of the substantia nigra towards PD diagnosis. In the experiments, even though the classification accuracy with the proposed feature extraction method and linear discriminant analysis is lower than that of expert physicians, the results suggest the potential of tensorial feature extraction.

Parkinson\'s Disease (PD) is a complex neurodegenerative disorder characterized by a spectrum of motor and non-motor symptoms, prominently featuring the freezing of gait (FOG), which significantly impairs patients\' quality of life. Despite extensive research, the precise mechanisms underlying FOG remain elusive, posing challenges for effective management and treatment. This paper presents a comprehensive meta-analysis of FOG prediction and detection methodologies, with a focus on the integration of wearable sensor technology and machine learning (ML) approaches. Through an exhaustive review of the literature, this study identifies key trends, datasets, preprocessing techniques, feature extraction methods, evaluation metrics, and comparative analyses between ML and non-ML approaches. The analysis also explores the utilization of cueing devices. The limited adoption of explainable AI (XAI) approaches in FOG prediction research represents a significant gap. Improving user acceptance and comprehension requires an understanding of the logic underlying algorithm predictions. Current FOG detection and prediction research has a number of limitations, which are identified in the discussion. These include issues with cueing devices, dataset constraints, ethical and privacy concerns, financial and accessibility restrictions, and the requirement for multidisciplinary collaboration. Future research avenues center on refining explainability, expanding and diversifying datasets, adhering to user requirements, and increasing detection and prediction accuracy. The findings contribute to advancing the understanding of FOG and offer valuable guidance for the development of more effective detection and prediction methodologies, ultimately benefiting individuals affected by PD.