Use of digital health technologies (DHT) in chronic disease management is rising. We aim to evaluate the impact of DHT on clinical outcomes from randomized controlled trials (RCTs) of patients with heart failure (HF) and diabetes mellitus (DM). Electronic databases were searched for DHT RCTs in patients with HF and DM until February 2021. Patient characteristics and outcomes were analyzed. One published (N = 519) and 6 registered (N = 3423) eligible studies were identified, with one study exclusively including HF and DM patients. Median DHT monitoring was 12 months, with six studies using mobile platforms as their key exposure. Clinical outcomes included quality-of-life or self-care surveys (n = 1 each), physical activity metrics, changes in biomarkers, and other clinical endpoints (n = 3). Limited data exist on RCTs evaluating DHT in patients with concomitant HF and DM. Further work should define standardized clinical endpoints and platforms that can manage patients with multiple comorbidities.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9153219 | PMC |
| http://dx.doi.org/10.1007/s12265-022-10273-6 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Engagement of adolescents with ADHD in a narrative-centered game-based behavior change environment to reduce alcohol use.
Front Educ (Lausanne)
January 2024
Division of Adolescent and Young Adult Medicine, Department of Pediatrics, University of California, San Francisco, San Francisco, CA, United States.
Background: Attention deficit hyperactivity disorder (ADHD) affects about 13% of adolescents and is associated with substance use-related morbidity and mortality. While evidence on effective interventions to reduce alcohol use among adolescents with ADHD is limited, parent-teen communication about alcohol use has been found to be protective. Other approaches, such as educational interventions, hold promise to reduce alcohol-related harms in adolescents with ADHD.
View Article and Find Full Text PDFSelf-sovereign management scheme of personal health record with personal data store and decentralized identifier.
Comput Struct Biotechnol J
November 2024
Intellicode Cooperation, Republic of Korea.
Conventional personal health record (PHR) management systems are centralized, making them vulnerable to privacy breaches and single points of failure. Despite progress in standardizing healthcare data with the FHIR format, hospitals often lack efficient platforms for transferring PHRs, leading to redundant tests and delayed treatments. To address these challenges, we propose a decentralized PHR management system leveraging Personal Data Stores (PDS) and Decentralized Identifiers (DIDs) in line with the Web 3.
View Article and Find Full Text PDFAssessing the Clinical and Functional Status of COPD Patients Using Speech Analysis During and After Exacerbation.
Int J Chron Obstruct Pulmon Dis
January 2025
Department of Cardiology, Respiratory Medicine and Intensive Care, University Hospital Augsburg, Augsburg, Germany.
Background: Chronic obstructive pulmonary disease (COPD) affects breathing, speech production, and coughing. We evaluated a machine learning analysis of speech for classifying the disease severity of COPD.
Methods: In this single centre study, non-consecutive COPD patients were prospectively recruited for comparing their speech characteristics during and after an acute COPD exacerbation.
Objective: This study was conducted to investigate the social media practices and attitudes towards e-professionalism among undergraduate medical students in a medical college of Pakistan.
Methods: This cross-sectional study was conducted on 220 undergraduate medical students from 2 to final-year MBBS, at CMH Lahore Medical College from March to August 2022. After ethical approval, a printed questionnaire was distributed among students, selected by stratified random sampling technique.
A novel machine learning based framework for developing composite digital biomarkers of disease progression.
Front Digit Health
January 2025
Biostatistics and Research Decision Sciences, Merck & Co., Inc., Rahway, NJ, United States.
Background: Current methods of measuring disease progression of neurodegenerative disorders, including Parkinson's disease (PD), largely rely on composite clinical rating scales, which are prone to subjective biases and lack the sensitivity to detect progression signals in a timely manner. Digital health technology (DHT)-derived measures offer potential solutions to provide objective, precise, and sensitive measures that address these limitations. However, the complexity of DHT datasets and the potential to derive numerous digital features that were not previously possible to measure pose challenges, including in selection of the most important digital features and construction of composite digital biomarkers.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!