We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us

Download Mobile App




Cardiac Telemetry Improves AF Detection Following Stroke

By HospiMedica International staff writers
Posted on 23 Jul 2019
Print article
Image: An example of an electrocardiomatrix, with flagged events (Photo courtesy of U-M).
Image: An example of an electrocardiomatrix, with flagged events (Photo courtesy of U-M).
A new study describes how electrocardiogram (ECG) telemetry data is analyzed in a three-dimensional (3D) matrix to allow for more accurate P-wave analysis.

Developed at the University of Michigan (U-M; Ann Arbor, USA), electrocardiomatrix is designed to convert two-dimensional signals from a patient’s ECG into a 3D heatmap so as to provide fast, intuitive detection of cardiac arrhythmias. To test the technology, U-M researchers conducted a prospective, observational study that analyzed data from 265 ischemic stroke and transient ischemic attack (TIA) patients between April 2017 and January 2018. Atrial fibrillation (AF) episodes lasting more than 30 seconds were identified through review of electrocardiomatrix matrices by a non-cardiologist.

The electrocardiomatrix results were then compared with AF identified directly by a cardiologist through standard telemetry. The results revealed that electrocardiomatrix successfully identified AF in 260 (98%) of cases. The positive predictive value of electrocardiomatrix compared with the clinical documentation was 86% overall, and 100% among a subset of patients with no history of AF. For the five false-positive and five false-negative cases, expert overview disagreed with the clinical documentation and confirmed the electrocardiomatrix-based diagnosis. The study was published on July 1, 2019, in Stroke.

“Electrocardiomatrix goes further than standard cardiac telemetry by examining large amounts of telemetry data in a way that's so detailed it's impractical for individual clinicians to attempt,” said senior author and electrocardiomatrix co-inventor Jimo Borjigin, PhD, of the department of molecular and integrative physiology at U-M Medical School. “Importantly, the electrocardiomatrix identification method was highly accurate for the 212 patients who did not have a history of AF. This group is most clinically relevant, because of the importance of determining whether stroke patients have previously undetected AF.”

“After a stroke, neurologists are tasked with identifying which risk factors may have contributed in order to do everything possible to prevent another event. That makes detecting irregular heartbeat an urgent concern for these patients,” said lead author professor of neurology Devin Brown, MD. “As a physician can't reasonably review every single heartbeat, current monitoring technology flags heart rates that are too high. More accurate identification of AF should translate into more strokes prevented.”

Related Links:
University of Michigan

Gold Member
Real-Time Diagnostics Onscreen Viewer
GEMweb Live
Gold Member
Solid State Kv/Dose Multi-Sensor
AGMS-DM+
Silver Member
Compact 14-Day Uninterrupted Holter ECG
NR-314P
New
LED Phototherapy System
Bililed Mini+

Print article

Channels

Surgical Techniques

view channel
Image: The living replacement knee will be tested in clinical trials within five years (Photo courtesy of ARPA-H)

Living Knee Replacement to Revolutionize Osteoarthritis Treatment

Osteoarthritis is the most prevalent type of arthritis, characterized by the progressive deterioration of cartilage, or the protective tissue covering the bone ends, resulting in pain, stiffness, and impaired... Read more

Patient Care

view channel
Image: The newly-launched solution can transform operating room scheduling and boost utilization rates (Photo courtesy of Fujitsu)

Surgical Capacity Optimization Solution Helps Hospitals Boost OR Utilization

An innovative solution has the capability to transform surgical capacity utilization by targeting the root cause of surgical block time inefficiencies. Fujitsu Limited’s (Tokyo, Japan) Surgical Capacity... Read more

Health IT

view channel
Image: First ever institution-specific model provides significant performance advantage over current population-derived models (Photo courtesy of Mount Sinai)

Machine Learning Model Improves Mortality Risk Prediction for Cardiac Surgery Patients

Machine learning algorithms have been deployed to create predictive models in various medical fields, with some demonstrating improved outcomes compared to their standard-of-care counterparts.... Read more

Point of Care

view channel
Image: The new eye-safe laser technology can diagnose traumatic brain injury (Photo courtesy of 123RF)

Novel Diagnostic Hand-Held Device Detects Known Biomarkers for Traumatic Brain Injury

The growing need for prompt and efficient diagnosis of traumatic brain injury (TBI), a major cause of mortality globally, has spurred the development of innovative diagnostic technologies.... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.