Longitudinal qualitative assessment of meaningful symptoms and relevance of WATCH-PD digital measures for people with early Parkinson's.

Background: Longitudinal qualitative data on what matters to people with Parkinson's disease are lacking and needed to guide patient-centered clinical care and development of outcome measures.

Objective: To evaluate change over time in symptoms, impacts, and relevance of digital measures to monitor disease progression in early Parkinson's.

Methods: In-depth, online symptom mapping interviews were conducted with 33 people with early Parkinson's at baseline and 1 year later to evaluate (A) symptoms, (B) impacts, and (C) relevance of digital measures to monitor personally relevant symptoms.

Fox Insight: Most Bothersome Symptoms in Early-Stage Parkinson's Disease.

Background: Limited evidence exists regarding the meaningfulness of symptoms experienced in early Parkinson's disease (PD).

Objectives: To identify the most bothersome symptoms experienced by people with early PD, leveraging data from the Parkinson's Disease Patient Report of Problems (PD-PROP) questionnaire within the Fox Insight Study.

Methods: Individuals with a self-reported diagnosis of PD completed the PD-PROP questionnaire, reporting up to five most bothersome symptoms.

Users of chronic prescription opioids decrease in the first 12 months following bariatric surgery.

Objective: Obesity is an independent risk factor for chronic pain frequently treated with opioids. Our study investigated the effect of Roux-en-Y gastric bypass (RYGB) and vertical sleeve gastrectomy (VSG) on chronic opioid prescription use.

Methods: Using the IBM MarketScan database (2010-2017), we analyzed adult chronic opioid users who underwent bariatric surgery.

Accelerating Parkinson's Disease drug development with federated learning approaches.

Parkinson's Disease is a progressive neurodegenerative disorder afflicting almost 12 million people. Increased understanding of its complex and heterogenous disease pathology, etiology and symptom manifestations has resulted in the need to design, capture and interrogate substantial clinical datasets. Herein we advocate how advances in the deployment of artificial intelligence models for Federated Data Analysis and Federated Learning can help spearhead coordinated and sustainable approaches to address this grand challenge.

Defining blood deserts and access to blood products for 660 million people: a geospatial analysis of eight states in Northern India.

Introduction: Blood transfusion is crucial, but low-income and middle-income countries like India face a severe shortage of banked blood. This study focuses on the Empowered Action Group (EAG) states in India, where healthcare is limited, and health outcomes are poor. Our objective was to assess the blood banking infrastructure and access to blood products in these states.