A Case of Acute-Onset, Refractory Freezing of Gait Following Subthalamic Nucleus Deep Brain Stimulation Adjustment.

Freezing of gait (FoG) is a disabling symptom of Parkinson's disease (PD) characterized by involuntary cessation/reduction. While deep brain stimulation (DBS) targeting the subthalamic nucleus (STN) effectively treats common PD symptoms such as tremor, its impact on FoG is less clear. Rarely, STN-DBS itself can induce FoG.

An Experimental Approach for Investigating Freezing of Gait in Parkinson's Disease Using Virtual Reality and Neural Sensing: A Pilot Study.

Freezing of gait (FOG) is a disabling symptom associated with Parkinson's disease (PD). Its understanding and effective treatment is compromised due to the difficulty in reliably triggering FOG in clinical and laboratory environments. The Cleveland Clinic-Virtual Home Environment (CC-VHE) platform was developed to address the challenges of eliciting FOG by combining an omnidirectional treadmill with immersive virtual reality (VR) environments to induce FOG under physical, emotional, and cognitive triggers.

Including individuals with Parkinson's disease and deep brain stimulation in rehabilitation trials: feasibility, challenges, and preliminary gait and postural stability results.

Background: People with Parkinson's disease (PwPD) who have undergone deep brain stimulation (DBS) surgery have been historically excluded from rehabilitation clinical trials.

Objective: This project investigated the safety, feasibility, and preliminary efficacy of a dual-task training intervention aimed at improving postural instability and gait dysfunction (PIGD) in PwPD with DBS.

Methods: Symptoms of PIGD were measured with the 2-Minute Walk Test (2MWT) and Timed Up and Go (TUG) test under single- and dual-task conditions.

Validation of the Comprehensive Augmented Reality Testing Platform to Quantify Parkinson's Disease Fine Motor Performance.

: Technological approaches for the objective, quantitative assessment of motor functions have the potential to improve the medical management of people with Parkinson's disease (PwPD), offering more precise, data-driven insights to enhance diagnosis, monitoring, and treatment. Markerless motion capture (MMC) is a promising approach for the integration of biomechanical analysis into clinical practice. The aims of this project were to evaluate a commercially available MMC system, develop and validate a custom MMC data processing algorithm, and evaluate the effectiveness of the algorithm in discriminating fine motor performance between PwPD and healthy controls (HCs).

Accelerated symptom improvement in Parkinson's disease via remote internet-based optimization of deep brain stimulation therapy: a randomized controlled multicenter trial.

Background: Deep brain stimulation (DBS) has emerged as an important therapeutic intervention for neurological and neuropsychiatric disorders. After initial programming, clinicians are tasked with fine-tuning DBS parameters through repeated in-person clinic visits. We aimed to evaluate whether DBS patients achieve clinical benefit more rapidly by incorporating remote internet-based adjustment (RIBA) of stimulation parameters into the continuum of care.

Parkinson's disease subtypes and their association with probable rapid eye movement sleep behavior disorder severity: a brainstem tractography and machine learning investigation.

Rapid Eye Movement (REM) sleep behavior disorder (RBD) affects nearly half of Parkinson's disease (PD) patients. However, the structural heterogeneity within the brainstem, which regulates REM sleep, remains largely unexplored in PD. Our objective was to identify distinct PD subtypes based on microstructural characteristics in the brainstem and examine their associations with the severity of RBD.

Neuroanatomical heterogeneity drives divergent cognitive and motor trajectories in Parkinson's disease subtypes.

Introduction: Cognitive symptoms of Parkinson's disease (PD) may initially present subtly, often overshadowed by more noticeable motor symptoms. However, as PD progresses, predicting which individuals will experience significant cognitive decline becomes challenging due to variability, suggesting distinct PD subtypes with varying cognitive trajectories. This study aimed to identify early PD subtypes based on patterns of gray matter atrophy in brain regions associated with cognition and assess their distinct patterns of cognitive change over time.

An augmented reality dual-task intervention improves postural stability in individuals with Parkinson's disease.

Background: The Dual-task Augmented Reality Treatment (DART) trial recently established that dual-task training (DTT) delivered by a physical therapist or the augmented reality DART platform was effective in improving spatiotemporal gait parameters under single- and dual-task conditions in individuals with Parkinson's disease (PD). Data regarding postural stability were not reported in the primary outcome manuscript.

Objective: The aim of this secondary analysis was to compare the effects of a Traditional DTT intervention delivered by a physical therapist and DTT delivered by the DART platform on postural stability, functional mobility, and turning in individuals with PD.

Standardizing default electronic health record tools to improve safety for hospitalized patients with Parkinson's disease.

Electronic Health Record (EHR) systems are often configured to address challenges and improve patient safety for persons with Parkinson's disease (PWP). For example, EHR systems can help identify Parkinson's disease (PD) patients across the hospital by flagging a patient's diagnosis in their chart, preventing errors in medication and dosing through the use of clinical decision support, and supplementing staff education through care plans that provide step-by-step road maps for disease-based care of a specific patient population. However, most EHR-based solutions are locally developed and, thus, difficult to scale widely or apply uniformly across hospital systems.

Optimization of inpatient medication administration among persons with Parkinson's disease: recommendations on pharmacy technology and workflow.

Individuals with Parkinson's disease (PD) are vulnerable during hospitalizations due to the underlying complexities o1f symptoms, and acute illness or medication changes often lead to decompensation. Complications during hospitalizations are often due to worsening motor and nonmotor symptoms and commonly result from inaccurate medication regimens. Although the accuracy of medication administration relies on an interplay of factors, including patient status, transitions of care, coordination between the hospital prescriber and outpatient neurologist, etc.

MRI-based multivariate gray matter volumetric distance for predicting motor symptom progression in Parkinson's disease.

While Parkinson's disease (PD)-related neurodegeneration is associated with structural changes in the brain, conventional magnetic resonance imaging (MRI) has proven less effective for clinical diagnosis due to its inability to reliably identify subtle changes early in the disease course. In this study, we aimed to develop a structural MRI-based biomarker to predict the rate of progression of motor symptoms in the early stages of PD. The study included 88 patients with PD and 120 healthy controls from the Parkinson's Progression Markers Initiative database; MRI at baseline and motor symptom scores assessed using the MDS-UPDRS-III at two time points (baseline and 48 months) were selected.

End of life care of hospitalized patients with Parkinson disease: a retrospective analysis and brief review.

Background: Towards the end of life (EOL), persons with parkinsonism (PwP) have complex needs and can present with unique palliative care (PC) challenges. There are no widely accepted guidelines to aid neurologists, hospitalists, or PC clinicians in managing the symptoms of PwP at EOL. We examined a population of PwP at EOL, aiming to describe trends of in-hospital management and utilization of PC services.

The Parkinson's disease waiting room of the future: measurements, not magazines.

Utilizing technology to precisely quantify Parkinson's disease motor symptoms has evolved over the past 50 years from single point in time assessments using traditional biomechanical approaches to continuous monitoring of performance with wearables. Despite advances in the precision, usability, availability and affordability of technology, the "gold standard" for assessing Parkinson's motor symptoms continues to be a subjective clinical assessment as none of these technologies have been fully integrated into routine clinical care of Parkinson's disease patients. To facilitate the integration of technology into routine clinical care, the Develop with Clinical Intent (DCI) model was created.

A Randomized Clinical Trial to Evaluate a Digital Therapeutic to Enhance Gait Function in Individuals With Parkinson's Disease.

Background: Postural instability and gait dysfunction (PIGD) is a cardinal symptom of Parkinson's disease (PD) and is exacerbated under dual-task conditions. Dual-task training (DTT), enhances gait performance, however it is time and cost intensive. Digitizing DTT via the Dual-task Augmented Reality Treatment (DART) platform can expand the availability of an effective intervention to address PIGD.

Interim Safety Profile From the Feasibility Study of the BrainGate Neural Interface System.

Background And Objectives: Brain-computer interfaces (BCIs) are being developed to restore mobility, communication, and functional independence to people with paralysis. Though supported by decades of preclinical data, the safety of chronically implanted microelectrode array BCIs in humans is unknown. We report safety results from the prospective, open-label, nonrandomized BrainGate feasibility study (NCT00912041), the largest and longest-running clinical trial of an implanted BCI.

Digitizing a Therapeutic: Development of an Augmented Reality Dual-Task Training Platform for Parkinson's Disease.

Augmented reality (AR) may be a useful tool for the delivery of dual-task training. This manuscript details the development of the Dual-task Augmented Reality Treatment (DART) platform for individuals with Parkinson's disease (PD) and reports initial feasibility, usability, and efficacy of the DART platform in provoking dual-task interference in individuals with PD. The DART platform utilizes the head-mounted Microsoft HoloLens2 AR device to deliver concurrent motor and cognitive tasks.

Oral ENT-01 Targets Enteric Neurons to Treat Constipation in Parkinson Disease : A Randomized Controlled Trial.

Background: Parkinson disease (PD) is associated with α-synuclein (αS) aggregation within enteric neurons. ENT-01 inhibits the formation of αS aggregates and improved constipation in an open-label study in patients with PD.

Objective: To evaluate the safety and efficacy of oral ENT-01 for constipation and neurologic symptoms in patients with PD and constipation.