Utilizing kinematic analysis of postural instability as an objective measure to aid in distinguishing between normal pressure hydrocephalus and Parkinson's disease.

Objective: Patients with normal pressure hydrocephalus (NPH) and Parkinson's Disease (PD) can clinically appear quite similar at baseline evaluation. We sought to investigate the use of kinematic assessment of postural instability (PI) using inertial measurement units (IMUs) as a mechanism of differentiation between the two disease processes. Methods: 20 patients with NPH, 55 patients with PD, and 56 age-matched, healthy controls underwent quantitative pull test examinations while wearing IMUs at baseline. Center of mass and foot position data were used to compare velocity and acceleration profiles, pull test step length, and reaction times between groups and as a function of Unified Parkinson's disease Rating Scale Pull Test (UPDRSPT) score. Results: Overall, the reactive postural response of NPH patients was characterized by slower reaction times and smaller steps compared to both PD patients and healthy controls. However, when patients were grouped by UPDRSPT scores, no reliable objective difference between groups was detected. Conclusion: At their initial evaluation, very few NPH patients demonstrate "normal" or "mild" PI as they appear to be older upon presentation compared to PD patients. As a result, kinematic assessment utilizing IMUs may not be helpful for differentiating between NPH and PD as a function of UPDRSPT score, but rather as a more fine-tuned method to define disease progression. We emphasize the need for further evaluation of incorporating objective kinematic data collection as a way to evaluate PI and improve patient outcomes.

Real world validation of activity recognition algorithm and development of novel behavioral biomarkers of falls in aged control and movement disorder patients.

The use of wearable sensors in movement disorder patients such as Parkinson's disease (PD) and normal pressure hydrocephalus (NPH) is becoming more widespread, but most studies are limited to characterizing general aspects of mobility using smartphones. There is a need to accurately identify specific activities at home in order to properly evaluate gait and balance at home, where most falls occur. We developed an activity recognition algorithm to classify multiple daily living activities including high fall risk activities such as sit to stand transfers, turns and near-falls using data from 5 inertial sensors placed on the chest, upper-legs and lower-legs of the subjects. The algorithm is then verified with ground truth by collecting video footage of our patients wearing the sensors at home. Our activity recognition algorithm showed >95% sensitivity in detection of activities. Extracted features from our home monitoring system showed significantly better correlation (~69%) with prospectively measured fall frequency of our subjects compared to the standard clinical tests (~30%) or other quantitative gait metrics used in past studies when attempting to predict future falls over 1 year of prospective follow-up. Although detecting near-falls at home is difficult, our proposed model suggests that near-fall frequency is the most predictive criterion in fall detection through correlation analysis and fitting regression models.

Hmong microbiome ANd Gout, Obesity, Vitamin C (HMANGO-C): A phase II clinical study protocol.

BACKGROUND: Hmong men in Minnesota exhibit a high prevalence of gout and hyperuricemia. Although evidence of vitamin C's effectiveness as a treatment for gout is mixed, analysis of therapeutic benefit based on an individual's multiomic signature may identify predictive markers of treatment success. OBJECTIVES: The primary objective of the Hmong Microbiome ANd Gout, Obesity, Vitamin C (HMANGO-C) study was to assess the effectiveness of vitamin C on serum urate in Hmong adults with and without gout/hyperuricemia. The secondary objectives were to assess if 1) vitamin C impacts the taxonomic and functional patterns of microbiota; 2) taxonomic and functional patterns of microbiota impact vitamin C's urate-lowering effects; 3) genetic variations impact vitamin C's urate-lowering effects; 4) differential microbial biomarkers exist for patients with or without gout; and 5) there is an association between obesity, gut microbiota and gout/hyperuricemia. METHODS: This prospective open-labelled clinical trial was guided by community-based participatory research principles and conducted under research safety restrictions for SARS-CoV-2. We aimed to enroll a convenient sample of 180 Hmong adults (120 with gout/hyperuricemia and 60 without gout/hyperuricemia) who provided medical, demographic, dietary and anthropometric information. Participants took vitamin C 500mg twice daily for 8 weeks and provided pre-and post- samples of blood and urine for urate measurements as well as stool samples for gut microbiome. Salivary DNA was also collected for genetic markers relevant to uric acid disposition. EXPECTED RESULTS: We expected to quantify the impact of vitamin C on serum urate in Hmong adults with and without gout/hyperuricemia. The outcome will enhance our understanding of how gut microbiome and genomic variants impact the urate-lowering of vitamin C and associations between obesity, gut microbiota and gout/hyperuricemia. Ultimately, findings may improve our understanding of the causes and potential interventions that could be used to address health disparities in the prevalence and management of gout in this underserved population. TRIAL REGISTRATION: ClinicalTrials.gov NCT04938024 (first posted: 06/24/2021).