Serum neurofilament indicates accelerated neurodegeneration and predicts mortality in late-stage Parkinson's disease.

Different stages of Parkinson's disease (PD) are defined by clinical criteria, while late-stage PD is marked by the onset of morbidity milestones and rapid clinical deterioration. Based on neuropathological evidence, degeneration in the dopaminergic system occurs primarily in the early stage of PD, raising the question of what drives disease progression in late-stage PD. This study aimed to investigate whether late-stage PD is associated with increased neurodegeneration dynamics rather than functional decompensation using the blood-based biomarker serum neurofilament light chain (sNfL) as a proxy for the rate of neurodegeneration.

Morbidity Milestones Demonstrate Long Disability-Free Survival in Parkinson's Disease Patients with Deep Brain Stimulation of the Subthalamic Nucleus.

Background: Deep brain stimulation of the subthalamic nucleus (STN-DBS) is an effective treatment for Parkinson's disease (PD). The long-term benefit in PD patients with STN-DBS in comparison to medical treatment (MT) alone has not yet been demonstrated conclusively.

Objectives: To judge the long-term outcome of patients with STN-DBS.

The Gut Dysmotility Questionnaire for Parkinson's disease: Insights into development and pretest studies.

Objective: A total of 48% of patients with Parkinson's disease (PD) present symptoms of gastrointestinal dysfunction, particularly constipation. Furthermore, gastrointestinal tract (GIT)-related non-motor symptoms (NMSs) appear at all stages of PD, can be prodromal by many years and have a relevant impact on the quality of life. There is a lack of GIT-focused validated tools specific to PD to assess their occurrence, progress, and response to treatment.

Gastrointestinal barriers to levodopa transport and absorption in Parkinson's disease.

Levodopa is the gold standard for the symptomatic treatment of Parkinson's disease (PD). There are well documented motor and non-motor fluctuations, however, that occur almost inevitably once levodopa is started after a variable period in people with PD. Whilst brain neurodegenerative processes play a part in the pathogenesis of these fluctuations, a range of barriers across the gastrointestinal (GI) tract can alter levodopa pharmacokinetics, ultimately contributing to non-optimal levodopa response and symptoms fluctuations.

The use of wearables for the diagnosis and treatment of Parkinson's disease.

Parkinson's disease (PD) is the second most common neurodegenerative disorder, with increasing numbers of affected patients. Many patients lack adequate care due to insufficient specialist neurologists/geriatricians, and older patients experience difficulties traveling far distances to reach their treating physicians. A new option for these obstacles would be telemedicine and wearables.

Modified Borggreve-Van Nes-Winkelmann rotationplasty for surgery in developing countries.

Background: Amputation is still the most common therapy for patients suffering from osteosarcoma in Myanmar, despite the fact that limb salvage surgery e.g. Borggreve-Van Nes-Winkelmann rotationplasty for malignant tumors located within the distal femur or proximal tibia is the current state-of-the-art reconstructive procedure.

Serum neurofilament indicates that DBS surgery can cause neuronal damage whereas stimulation itself does not.

Deep brain stimulation (DBS) is a potent symptomatic therapy for Parkinson's disease, but it is debated whether it causes or prevents neurodegeneration. We used serum neurofilament light chain (NFL) as a reporter for neuronal damage and found no difference between 92 patients with chronic STN-DBS and 57 patients on best medical treatment. Serum NFL transiently increased after DBS surgery whereas the initiation of STN stimulation did not affect NFL levels, suggesting that DBS surgery can be associated with neuronal damage whereas stimulation itself is not.

Parkinson's Disease Detection Based on Running Speech Data From Phone Calls.

Objective: Parkinson's Disease (PD) is a progressive neurodegenerative disorder, manifesting with subtle early signs, which, often hinder timely and early diagnosis and treatment. The development of accessible, technology-based methods for longitudinal PD symptoms tracking in daily living, offers the potential for transforming disease assessment and accelerating diagnosis.

Methods: A privacy-aware method for classifying patients and healthy controls (HC), on the grounds of speech impairment present in PD, is proposed.

Predictors of short-term impulsive and compulsive behaviour after subthalamic stimulation in Parkinson disease.

Background: The effects of subthalamic stimulation (subthalamic nucleus-deep brain stimulation, STN-DBS) on impulsive and compulsive behaviours (ICB) in Parkinson's disease (PD) are understudied.

Objective: To investigate clinical predictors of STN-DBS effects on ICB.

Methods: In this prospective, open-label, multicentre study in patients with PD undergoing bilateral STN-DBS, we assessed patients preoperatively and at 6-month follow-up postoperatively.

Rotigotine Transdermal Patch for Motor and Non-motor Parkinson's Disease: A Review of 12 Years' Clinical Experience.

Motor and non-motor symptoms (NMS) have a substantial effect on the health-related quality of life (QoL) of patients with Parkinson's disease (PD). Transdermal therapy has emerged as a time-tested practical treatment option, and the rotigotine patch has been used worldwide as an alternative to conventional oral treatment for PD. The efficacy of rotigotine on motor aspects of PD, as well as its safety and tolerability profile, are well-established, whereas its effects on a wide range of NMS have been described and studied but are not widely appreciated.

Assistive HCI-Serious Games Co-design Insights: The Case Study of i-PROGNOSIS Personalized Game Suite for Parkinson's Disease.

Human-Computer Interaction (HCI) and games set a new domain in understanding people's motivations in gaming, behavioral implications of game play, game adaptation to player preferences and needs for increased engaging experiences in the context of HCI serious games (HCI-SGs). When the latter relate with people's health status, they can become a part of their daily life as assistive health status monitoring/enhancement systems. Co-designing HCI-SGs can be seen as a combination of art and science that involves a meticulous collaborative process.

Assessment of real life eating difficulties in Parkinson's disease patients by measuring plate to mouth movement elongation with inertial sensors.

Parkinson's disease (PD) is a neurodegenerative disorder with both motor and non-motor symptoms. Despite the progressive nature of PD, early diagnosis, tracking the disease's natural history and measuring the drug response are factors that play a major role in determining the quality of life of the affected individual. Apart from the common motor symptoms, i.

Unobtrusive detection of Parkinson's disease from multi-modal and in-the-wild sensor data using deep learning techniques.

Parkinson's Disease (PD) is the second most common neurodegenerative disorder, affecting more than 1% of the population above 60 years old with both motor and non-motor symptoms of escalating severity as it progresses. Since it cannot be cured, treatment options focus on the improvement of PD symptoms. In fact, evidence suggests that early PD intervention has the potential to slow down symptom progression and improve the general quality of life in the long term.

Emotional well-being and pain could be a greater determinant of quality of life compared to motor severity in cervical dystonia.

Non-motor symptoms (NMS) occur in patients with cervical dystonia (CD) but with variable frequencies and impact on health-related quality of life (HRQoL). To define non-motor and motor profiles and their respective impact on HRQoL in CD patients using the newly validated Dystonia Non-Motor Symptoms Questionnaire (DNMSQuest). In an observational prospective multicentre case-control study, we enrolled 61 patients with CD and 61 age- and sex-matched healthy controls (HC) comparing demographic data, motor and non-motor symptoms and HRQoL measurements.

Smartwatch-based Activity Analysis During Sleep for Early Parkinson's Disease Detection.

Parkinson's Disease (PD) is the second most common neurodegenerative disorder with the non-motor symptoms preceding the motor impairment that is needed for clinical diagnosis. In the current study, an angle-based analysis that processes activity data during sleep from a smartwatch for quantification of sleep quality, when applied on controls and PD patients, is proposed. Initially, changes in their arm angle due to activity are captured from the smartwatch triaxial accelerometry data and used for the estimation of the corresponding binary state (awake/sleep).

Using IMU Sensors to Assess Motor Degradation of PD Patients by Modeling In-meal Plate-to-Mouth Movement Elongation.

Parkinson's disease (PD) is the second most common age-related neurodegenerative disorder after Alzheimer's disease, associated, among others, with motor symptoms such as resting tremor, rigidity and bradykinesia. At the same time, early diagnosis of PD is hindered by a high misdiagnosis rate and the subjective nature of the diagnosis process itself. Recent developments in mobile and wearable devices, such as smartphones and smartwatches, have allowed the automated detection and objective measurement of PD symptoms.

Parcellation of the Subthalamic Nucleus in Parkinson's Disease: A Retrospective Analysis of Atlas- and Diffusion-Based Methods.

Background: Deep brain stimulation (DBS) is an established method of treatment for Parkinson's disease (PD). A stimulation sweet spot at the interface between the motor and associative clusters of the subthalamic nucleus (STN) has recently been postulated. The aim of this study was to analyze the available clustering methods for the STN and their correlation to outcome.

Screening of Parkinsonian subtle fine-motor impairment from touchscreen typing via deep learning.

Fine-motor impairment (FMI) is progressively expressed in early Parkinson's Disease (PD) patients and is now known to be evident in the immediate prodromal stage of the condition. The clinical techniques for detecting FMI may not be robust enough and here, we show that the subtle FMI of early PD patients can be effectively estimated from the analysis of natural smartphone touchscreen typing via deep learning networks, trained in stages of initialization and fine-tuning. In a validation dataset of 36,000 typing sessions from 39 subjects (17 healthy/22 PD patients with medically validated UPDRS Part III single-item scores), the proposed approach achieved values of area under the receiver operating characteristic curve (AUC) of 0.

Lower Energy Intake among Advanced vs. Early Parkinson's Disease Patients and Healthy Controls in a Clinical Lunch Setting: A Cross-Sectional Study.

Unintentional weight loss has been observed among Parkinson's disease (PD) patients. Changes in energy intake (EI) and eating behavior, potentially caused by fine motor dysfunction and eating-related symptoms, might contribute to this. The primary aim of this study was to investigate differences in objectively measured EI between groups of healthy controls (HC), early (ESPD) and advanced stage PD patients (ASPD) during a standardized lunch in a clinical setting.

Differences in neurology residency training programmes across Europe - a survey among the Residents and Research Fellow Section of the European Academy of Neurology national representatives.

Background And Purpose: Neurology is rapidly evolving as a result of continuous diagnostic and therapeutic progress, which influences the daily work of neurologists. Therefore, updating residency training programmes is crucial for the future of neurology. Several countries are currently discussing and/or modifying the structure of their neurology residency training programme.

[Dystonia Non-Motor Symptoms Questionnaire (DNMSQuest) for assessment of non-motor symptoms in dystonia : Intercultural adaptation in the German language].

Background: Non-motor symptoms (NMS) in patients with dystonia have a relevant impact on health-related quality of life; however, a comprehensive easy to use NMS assessment tool for clinical bedside use is currently not available.

Objective: The validated German version of the dystonia non-motor symptoms questionnaire (DNMSQuest) for assessing NMS in craniocervical dystonia is presented.

Methods: The DNMSQuest in the German language was developed based on internationally recognized standards for intercultural adaptation of self-completed patient questionnaires.

Multiple-Instance Learning for In-The-Wild Parkinsonian Tremor Detection.

Parkinson's Disease (PD) is a neurodegenerative disorder that manifests through slowly progressing symptoms, such as tremor, voice degradation and bradykinesia. Automated detection of such symptoms has recently received much attention by the research community, owing to the clinical benefits associated with the early diagnosis of the disease. Unfortunately, most of the approaches proposed so far, operate under a strictly laboratory setting, thus limiting their potential applicability in real world conditions.

Early Parkinson's Disease Detection via Touchscreen Typing Analysis using Convolutional Neural Networks.

Parkinson's Disease (PD) is the second most common neurodegenerative disorder worldwide, causing both motor and non-motor symptoms. In the early stages, symptoms are mild and patients may ignore their existence. As a result, they do not undergo any related clinical examination; hence delaying their PD diagnosis.

Detecting Parkinsonian Tremor From IMU Data Collected in-the-Wild Using Deep Multiple-Instance Learning.

Parkinson's Disease (PD) is a slowly evolving neurological disease that affects about [Formula: see text] of the population above 60 years old, causing symptoms that are subtle at first, but whose intensity increases as the disease progresses. Automated detection of these symptoms could offer clues as to the early onset of the disease, thus improving the expected clinical outcomes of the patients via appropriately targeted interventions. This potential has led many researchers to develop methods that use widely available sensors to measure and quantify the presence of PD symptoms such as tremor, rigidity and braykinesia.