View clinical trials related to Parkinsonian Disorders.
Filter by:Sleep-wake disturbances are a major factor associated with reduced quality of life of individuals with Parkinson's disease (PD), a progressive neurological disorder affecting millions of people in the U.S and worldwide. The brain mechanisms underlying these sleep disorders, and the effects of therapeutic interventions such as deep brain stimulation on sleep-related neuronal activity and sleep behavior, are not well understood. Results from this study will provide a better understanding of the brain circuitry involved in disordered sleep in PD and inform the development of targeted therapeutic interventions to treat sleep disorders in people with neurodegenerative disease.
In Parkinson's disease (PD) patients undergoing standard-of-care Deep Brain Stimulation (DBS) therapy, to compare the effect on Parkinson's symptoms of two different neurostimulator settings designed to differ from each other as much as possible with respect to how much they activate two different neuroanatomical structures: the axonal pathway from Globus Pallidus (GP) to Pedunculopontine Nucleus (PPN), and the axonal pathway from PPN to GP.
Background: Falls are common in elderly individuals and those with neurological conditions like Parkinson's disease. Parkinson's disease causes postural instability and mobility issues that lead to falls and reduced quality of life. The fear of falling (FoF), a natural response to unstable balance, can exacerbate postural control problems. However, evaluating FoF relies primarily on subjective self-reports due to a lack of objective assessment methods. Objectives: This mixed-methods feasibility study aims to develop an objective method for assessing fear of falling during motion and walking using virtual reality. This protocol examines a range of FoF-related responses, including cognitive, neuromuscular, and postural stability factors. Methods: Individuals without and with Parkinson's disease will complete questionnaires, movement tasks, and walking assessments in real and virtual environments where FoF can be elicited using virtual reality (VR) technology. Data from center-of-pressure measurements, electromyography, heart rate monitoring, motion capture, and usability metrics will evaluate the method's acceptability and safety. Semi-structured interviews will gather participants' and researchers' experiences of the protocol. Discussion: This method may allow accurate assessment of how FoF impacts movement by measuring cognitive, neuromuscular, and postural responses during gait and motion. Virtual environments reproduce real-life scenarios that trigger FoF. Rigorously assessing FoF with this approach could demonstrate its ability to quantify the effects of FoF on movement. Conclusions: This protocol aims to improve FoF assessment by evaluating multiple responses during movement in virtual environments. It addresses current measures' limitations. A feasibility study will identify areas for improvement specific to Parkinson's disease. Successful validation could transform how FoF is evaluated and managed.
The purpose of this study is to test the performance of the AID-P across 21 sites in the Parkinson Study Group. Each site will perform imaging, clinical scales, diagnosis, and will upload the data to the web-based software tool. The clinical diagnosis will be blinded to the diagnostic algorithm and the imaging diagnosis will be compared to the movement disorders trained neurologist diagnosis.
The Movement Disorders Society (MDS) Unified Parkinson's Disease Rating Scale (UPDRS) Part III (MDS-UPDRS III) is the primary assessment method for motor symptoms in Parkinson's disease patients. Currently, movement disorder specialists conduct semi-quantitative scoring, which entails limitations such as subjectivity, weak sensitivity, and a limited number of professional physicians. This study, based on machine vision, establishes gold standard labels according to expert scoring. By using machine learning, we develop a machine rating model and compare the model's performance with gold standard rating and general clinical rating to investigate the accuracy of machine vision-based MDS-UPDRS III machine rating.
In this study, the investigators will assess the Vagus nerve in two groups: Group 1 which include patients with parkinsonism and group 2 which included age and sex matched healthy control. The aim of the study is: detecting the difference between both groups and correlating the changes in the Vagus nerve cross sectional area with the motor and non motor manifestations of parkinsonism
This project aims to investigate whether an integrated model based on proactive and reactive telenursing monitoring coordinated by a parkinsonism nurse specialist (case manager) is able to improve care delivery and quality of life of patients with atypical parkinsonisms. This could reduce the risk (e.g. through health education counselling) and the severity of complications (e.g. falls). Main responsibilities of the Co-PI: project idea and supervision, coordination of the study, patient selection and recruitment, patient recruitment, participation in statistical analysis and drafting the manuscript. Co-PI is responsible of the rate of recruitment and drop-out
The goal of this observational study is to learn about the impact of the different types of pain and of the domains involved in the autonomic disorders of inpatients and outpatients diagnosed with Parkinson disease (PD) and multiple system atrophy (MSA) admitted to Istituti Clinici Scientifici Maugeri Centers. The main aims are: Evaluate the prevalence of pain and characterize it in Parkinson's disease and atypical parkinsonisms (MSA) Evaluate the effect of rehabilitation on pain and autonomic symptoms Evaluate the prevalence of autonomic symptoms in Parkinson's disease and atypical parkinsonisms (MSA) Assess the impact of pain and autonomic symptoms on quality of life. Participants will perform neurological examination, rehabilitation program and clinical scales. Researchers will compare the two groups of patients (PD and MSA) and the effect of the rehabilitation on pain, autonomic symptoms and quality of life.
Parkinson's Disease (PD) affects people universally, including all ethnic and socioeconomic groups, as a highly prevalent neurodegenerative disorder. However, there are several additional challenges for people living with PD in developing countries, especially those with low socioeconomic status. There is limited access to neurological care in Brazil due to an uneven distribution of neurologists and neurological facilities, which is more critical in the poorest regions. In addition, people in these vulnerable communities are more exposed to environmental pollution, including pesticides and metals used in agriculture and mining, respectively. Therefore, reliable data on the prevalence and incidence of PD in Brazil are essential to understand the proportion of this limited access to care for patients with PD, its burden in the region, and the potential role of environmental and lifestyle risk factors in PD. Unfortunately, the literature describes few epidemiological data on PD in Latin America, including Brazil, with an evident need for more information in their regions remarkably different. The investigators will carry out a population-based study in four municipalities in Brazil (Veranópolis-RS, Belém-PA, Jacobina-BA and Candangolândia-DF), comprising distinct communities in terms of ethnic groups, education levels, and environmental and lifestyle exposures, to portray the differences in Brazilian society. The present study will screen all people living in these regions aged 60 and over for parkinsonian symptoms and REM sleep behavior disorder (RBD). At least one neurologist will examine those selected to determine the diagnosis of PD or related disorders. The study also will evaluate a random sample of those individuals with a negative screen. Each participant selected after the screening will undergo clinical assessments and interview with the addition of a comprehensive questionnaire on clinical and sociodemographic data, prodromal symptoms, as well as lifestyle and environmental exposures, including occupational use and non-occupational use of pesticides and metals. An equal sample of blood and hair will be collected from individuals with PD and controls. The study will determine the prevalence of PD and related disorders in these distinct communities. An exploratory analysis also will be performed to determine the association between PD and each variable investigated.
Study Rationale: No accurate tests currently exist to diagnose Parkinson's disease (PD) and the conditions which mimic it (atypical parkinsonism) at a very early stage. Similarly there are no accurate ways to track how these diseases progress in a very precise manner. Recording eye movements and pupils may be a very sensitive way of doing this and may contain important information about a patient's diagnosis and their cognitive and motor function. Hypothesis: We hypothesize that measuring eye movements and pupil changes while people watch short video clips will differentiate PD and atypical parkinsonism at an early stage. We hypothesize that eye movements and pupil changes will be able to track how a person's disease changes over time and could even predict their disease course from the start. Before we can do this, we need to be able to accurately differentiate between PD and atypical parkinsonism and see how eye movements vary among people with the same disease. Study Design: We will ask a large number of people with PD and atypical parkinsonism to watch very brief video clips while we record eye movements and pupil responses. This is like changing the television channel every few seconds and observing what happens to a person's eyes as they search the new clip. We will compare these results between different disease groups and correlate them with clinical features of PD and atypical parkinsonism. Impact on Diagnosis/Treatment of Parkinson's disease: This may have enormous impact in the assessment of people with PD. It may become an important diagnostic tool, a prognostic marker at the early stage of disease, as well as providing the ability to track disease progression in clinical trials. Next Steps for Development: Once we can demonstrate that eye tracking can differentiate these conditions, we will follow a large number of patients to see how their eye movements and pupils change over time with their disease. If this is a reliable way to track disease it could be used to measure disease progression in these conditions and response to treatment.