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3,476 results for “Parkinson disease”
Association of specific biotypes in patients with Parkinson's disease and disease progression
<p><span><b>Objective </b></span></p> <p><span>To identify biotypes in newly diagnosed Parkinson's disease patients and test whether these biotypes could explain inter-individual differences in longitudinal progression. </span></p> <p><span><b>Methods</b></span></p> <p><span>In this longitudinal analysis, we use a data-driven approach clustering PD patients from the Parkinson's Progression Markers Initiative (PPMI) (n = 314, age = 61.0 ± 9.5, 34.1% female, 5 years follow-up). Voxel-level neuroanatomical features were estimated using deformation-based morphometry (DBM) of T1-weighted MRI. Voxels whose deformation values were significantly correlated (<i>P</i> < 0.01) with clinical scores (MDS-UPDRS-Parts I-III, MDS-UPDRS-total, tremor score, and postural instability and gait difficulty score) at baseline were selected. Then, these neuroanatomical features were subjected to hierarchical cluster analysis. Changes in the longitudinal progression and neuroanatomical pattern were compared between different biotypes. </span></p> <p><span><b>Results</b></span></p> <p><span>Two neuroanatomical biotypes were identified: (i) biotype 1 (n = 114) with subcortical brain volume as smaller than heathy controls; (ii) biotype 2 (n = 200) with subcortical brain volumes larger than heathy controls. Biotype 1 had more severe motor impairment, autonomic dysfunction, and very much worse REM sleep behavior disorder than biotype 2 at baseline. Although disease duration at initial visit and follow-up were similar between biotypes, PD patients with smaller subcortical brain volume had poorer prognosis, with more rapid decline in several clinical domains and in dopamine functional neuroimaging over an average of five years. </span></p> <p><span><b>Conclusion</b></span></p> <p><span>Robust neuroanatomical biotypes exist in PD with distinct clinical and neuroanatomical pattern. These biotypes can be detected at diagnosis, and predict the course of longitudinal progression, which should benefit trial design and evaluation.</span></p>
Figure 9 from: Klein A (2016) Crowdsourcing voice editing and quality assessment of data collected from the largest mobile phone-based research study of Parkinson disease. Research Ideas and Outcomes 2: e8848. https://doi.org/10.3897/rio.2.e8848
Figure 9 - Timeline. We will prepare and update the Web app (Aim 2) as we develop it for use in annotating gold standard audio data (Aim 1) and as we get feedback on its use in connection with Amazon's Mechanical Turk (Aim 2). Year 2 will consist primarily of testing the aggregation of annotated audio data for further analysis (Aim 2), to train an automated approach (Exploratory Aim), and to publish and present our findings.
Figure 2 from: Klein A (2016) Crowdsourcing voice editing and quality assessment of data collected from the largest mobile phone-based research study of Parkinson disease. Research Ideas and Outcomes 2: e8848. https://doi.org/10.3897/rio.2.e8848
Figure 2 - Mockup of audio recording annotation tool – Step 1: Selection. This figure shows a mockup of what an audio annotation Web application tool could look like. In this first step, (A) the Worker presses the Play icon to listen to the voice recording, (B) selects a problematic segment by clicking and dragging the mouse over the waveform, and (C) replays the recording if necessary and selects other problematic segments.
Figure 3 from: Klein A (2016) Visual Parkinson's Disease Rating Scale: A Universal Iconic Questionnaire for Epidemiological Studies in India. Research Ideas and Outcomes 2: e8834. https://doi.org/10.3897/rio.2.e8834
Figure 3 - Timeline This Gantt chart provides an estimate of the relative timing and duration for achieving each of the Aims.
Figure 1 from: Klein A (2016) Visual Parkinson's Disease Rating Scale: A Universal Iconic Questionnaire for Epidemiological Studies in India. Research Ideas and Outcomes 2: e8834. https://doi.org/10.3897/rio.2.e8834
Figure 1 - First pass at a VPDRS static graphic Figure 1 corresponds to the first self-administered MDS-UPDRS question: 1.7 SLEEP PROBLEMS. Over the past week, have you had trouble going to sleep at night or staying asleep through the night? Consider how rested you felt after waking up in the morning. 0: Normal: No problems. 1: Slight: Sleep problems are present but usually do not cause trouble getting a full night of sleep. 2: Mild: Sleep problems usually cause some difficulties getting a full night of sleep. 3: Moderate: Sleep problems cause a lot of difficulties getting a full night of sleep, but I still usually sleep for more than half the night. 4: Severe: I usually do not sleep for most of the night."
Figure 5 from: Klein A (2016) Crowdsourcing voice editing and quality assessment of data collected from the largest mobile phone-based research study of Parkinson disease. Research Ideas and Outcomes 2: e8848. https://doi.org/10.3897/rio.2.e8848
Figure 5 - DARPA-funded seedling project. This schematic represents our DARPA-funded seedling project to assess the feasibility of collecting phone voice recordings from PD patients for use in a competition.
Figure 4 from: Klein A (2016) Crowdsourcing voice editing and quality assessment of data collected from the largest mobile phone-based research study of Parkinson disease. Research Ideas and Outcomes 2: e8848. https://doi.org/10.3897/rio.2.e8848
Figure 4 - Audio recording annotation tool – Step 3: Rating. Following Figures 2 and 3, here the Worker rates how serious the problem is that is affecting the highlighted segment of the recording. In this example, the Worker indicates that the background noise (wind) is not good, but that it doesn't interfere with his/her ability to hear the voice in the recording.
Figure 7 from: Klein A (2016) Crowdsourcing voice editing and quality assessment of data collected from the largest mobile phone-based research study of Parkinson disease. Research Ideas and Outcomes 2: e8848. https://doi.org/10.3897/rio.2.e8848
Figure 7 - Example mPower patient voice data. In the mPower app, PD patients are prompted to perform the voice activity three times per day: once before taking their medication, a second time when they feel they are at their best after taking their medication, and a third "random" time. This figure shows example voice data for a single patient on medication (top) and at a "random" time, very likely off medication (bottom). On the left are waveforms, showing the acoustic voice signal over time (0-10 seconds), from which one can clearly see that the patient's voice trailed off to a minimum (bottom left) compared to after medication (top left). On the right are spectrograms, representing signal amplitude at different frequencies (0-5 kHz) over time (0-10 seconds). The spectrogram after medication (top right) has more uniform frequency bands across the recording compared to the rather "muddled" spectrogram recorded at the random time (bottom right).
Figure 3 from: Klein A (2016) Crowdsourcing voice editing and quality assessment of data collected from the largest mobile phone-based research study of Parkinson disease. Research Ideas and Outcomes 2: e8848. https://doi.org/10.3897/rio.2.e8848
Figure 3 - Audio recording annotation tool – Step 2: Annotation. Following Figure 2, here the Worker selects one or more categories describing why the highlighted segment in the audio waveform is problematic. In this example, there was a lot of background noise (wind).
Figure 6 from: Klein A (2016) Crowdsourcing voice editing and quality assessment of data collected from the largest mobile phone-based research study of Parkinson disease. Research Ideas and Outcomes 2: e8848. https://doi.org/10.3897/rio.2.e8848
Figure 6 - Android and iOS Parkinson app screenshots. Top: Android PD app screenshots showing instructions for the phonation (voice) task. Bottom: mPower PD app screenshots. Each participant in the mPower study is prompted to perform a voice activity three times a day. The rightmost screenshot demonstrates the visual feedback that is provided during audio recording, to try to keep the voice at the best amplitude for recording.
Figure 2 from: Klein A (2016) Visual Parkinson's Disease Rating Scale: A Universal Iconic Questionnaire for Epidemiological Studies in India. Research Ideas and Outcomes 2: e8834. https://doi.org/10.3897/rio.2.e8834
Figure 2 - Prototype for the mobile phone app This screen shows a pre-release version of Node, which will support the VPDRS/UPDRS modules. Here we present a means by which a person administering a questionnaire can securely log into and manipulate patient information locally and through cloud services and lastly an example clinician-administered UPDRS question.
Chinese Exercise Modalities in Parkinson's Disease
ClinicalTrials.gov study NCT00029809. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Repeated-Dose Oral N-acetylcysteine for the Treatment of Parkinson's Disease
ClinicalTrials.gov study NCT02212678. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Apathy in Parkinson Disease TMS Study
ClinicalTrials.gov study NCT06087926. IPD Sharing: YES. Countries: 1. Publications: 0.
Effect of Rotigotine on Motor Symptoms in Patients With Advanced Parkinson's Disease (PD) With Motor Fluctuations and Symptoms of Gastrointestinal Dysfunction
ClinicalTrials.gov study NCT01536015. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Effect of Levodopa on Cardiovascular Autonomic Function in Parkinson's Disease
ClinicalTrials.gov study NCT05487300. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
A Pilot Study of Suvorexant for Insomnia in Parkinson Disease
ClinicalTrials.gov study NCT02729714. IPD Sharing: Not stated. Countries: 1. Publications: 0.
An Open Label Extension Study of the Safety and Clinical Utility of IPX066 in Subjects With Parkinson's Disease
ClinicalTrials.gov study NCT01096186. IPD Sharing: NO. Countries: 10. Publications: 0.
An Open-Label Extension Trial to Assess the Safety of Long-Term Treatment of Rotigotine in Advance-Stage Parkinson's Disease
ClinicalTrials.gov study NCT00594386. IPD Sharing: Not stated. Countries: 2. Publications: 0.
Phase I, KM-819 in Healthy Subjects for Parkinson's Disease
ClinicalTrials.gov study NCT03022799. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
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