Background: Adults with transposition of the great arteries (TGA) after atrial switch repair have an increased risk for arrhythmia and sudden cardiac death. We analyzed whether a remote monitoring (RM) system as part of an implantable cardiac device contributes to timely recognition and improved treatment of critical arrhythmias in these patients.

Methods And Results: All consecutive TGA patients (n=11) requiring a pacemaker or cardiac resynchronization therapy with or without implantable cardioverter defibrillator between 2008 and 2011 were included. RM-detected arrhythmia, abnormality of device integrity and reaction time from event transmission until acknowledgement via email and clinical decision making were analyzed and compared to a control group (n=21). In 10 patients (91%) 17 arrhythmias were detected, 8 patients (80%) indicated no symptoms. In the RM group time interval from transmission to acknowledgement was 2.4 days (range, 0-4.5 days). Clinical decision-making was advanced by a mean of 77.5 days (range, 10-197 days) compared with conventional follow-up and identified adaption of anti-arrhythmic medication in 8, electrical cardioversion in 2, overdrive pacing in 1 and radiofrequency ablation in 2 patients. A coronary sinus lead fracture was identified in 1 patient followed by successful replacement.

Conclusions:  RM enables early detection of tachyarrhythmia followed by optimization of medical treatment and potentially life-saving anti-tachycardic intervention in adults after atrial repair of TGA.  

Download full-text PDF

Source
http://dx.doi.org/10.1253/circj.cj-13-0670DOI Listing

Publication Analysis

Top Keywords

remote monitoring
8
treatment critical
8
critical arrhythmias
8
adults atrial
8
atrial switch
8
transposition great
8
great arteries
8
transmission acknowledgement
8
days range
8
monitoring leads
4

Similar Publications

Cyanobacteria hot spot detection integrating remote sensing data with convolutional and Kolmogorov-Arnold networks.

Sci Total Environ

January 2025

Interdisciplinary Lab for Mathematical Ecology and Epidemiology & Department of Mathematical and Statistical Sciences, University of Alberta, Canada. Electronic address:

Prompt and accurate monitoring of cyanobacterial blooms is essential for public health management and understanding aquatic ecosystem dynamics. Remote sensing, in particular satellite observations, presents a good alternative for continuous monitoring. This study employs multispectral images from the Sentinel-2 constellation alongside ERA5-Land to enable broad-scale data acquisition.

View Article and Find Full Text PDF

Machine learning-based identification of animal feeding operations in the United States on a parcel-scale.

Sci Total Environ

January 2025

Department of Biological and Agricultural Engineering, University of Arkansas, United States of America. Electronic address:

The increasing global demand for meat and dairy products, fueled by rapid industrialization, has led to the expansion of Animal Feeding Operations (AFOs) in the United States (US). These operations, often found in clusters, generate large amounts of manure, posing a considerable risk to water quality due to the concentrated waste streams they produce. Accurately mapping AFOs is essential for effective environmental and disease management, yet many facilities remain undocumented due to variations in federal and state regulations.

View Article and Find Full Text PDF

Digital health interventions in adult intensive care and recovery after critical illness to promote survivorship care.

J Intensive Care Soc

January 2025

Department of Physiotherapy, Faculty of Medicine, Dentistry and Health Sciences, School of Health Sciences, The University of Melbourne, Melbourne, VIC, Australia.

Digital health refers to the field of using and developing technology to improve health outcomes. Digital health and digital health interventions (DHIs) within the area of intensive care and critical illness survivorship are rapidly evolving. Digital health interventions refer to technologies in clinical interventional format.

View Article and Find Full Text PDF

Background And Aims: Artificial Intelligence (AI) beginning to integrate in healthcare, is ushering in a transformative era, impacting diagnostics, altering personalized treatment, and significantly improving operational efficiency. The study aims to describe AI in healthcare, including important technologies like robotics, machine learning (ML), deep learning (DL), and natural language processing (NLP), and to investigate how these technologies are used in patient interaction, predictive analytics, and remote monitoring. The goal of this review is to present a thorough analysis of AI's effects on healthcare while providing stakeholders with a road map for navigating this changing environment.

View Article and Find Full Text PDF

Promoting Physical Activity in People With Parkinson's Disease Through a Smartphone App: A Pilot Study.

J Neurol Phys Ther

January 2025

Center of Expertise for Parkinson & Movement Disorders, Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, Gelderland, the Netherlands (S.S., N.M.V., S.K.L.D., B.R.B.); Harvard Medical School, Boston, Massachusetts (A.A., M.A.S., E.A.M.); Departments of Epidemiology and Nutrition, T. H. Chan School of Public Health, Harvard University, Boston, Massachusetts (A.A.); Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts (M.A.S., E.A.M.); Mass General Institute for Neurodegenerative Disease, Massachusetts General Hospital, Boston, Massachusetts (M.A.S.); and Biostatistics Center, Massachusetts General Hospital, Boston, Massachusetts (E.A.M.).

Background And Purpose: Physical activity has beneficial symptomatic effects for people with Parkinson's disease (PD), but increasing-and sustaining-a physically active lifestyle remains challenging. We investigated the feasibility (ability to increase step counts) and usability of a behavioral intervention using a motivational smartphone application to remotely increase physical activity in PD.

Methods: We performed a 4-week, double-blind pilot trial.

View Article and Find Full Text PDF

Want 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!