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
Detecto

Download Mobile App




Smartwatch Detection of Atrial Fibrillation Has Great Potential, Finds Study

By HospiMedica International staff writers
Posted on 14 Oct 2022
Print article
Image: Better algorithms and machine learning can help smartwatches improve detection of atrial fibrillation (Photo courtesy of Pexels)
Image: Better algorithms and machine learning can help smartwatches improve detection of atrial fibrillation (Photo courtesy of Pexels)

Extended cardiac monitoring in patients and the use of implantable cardiovascular electronic devices can increase detection of atrial fibrillation (AF), but the devices have limitations including short battery life and lack of immediate feedback. Can new smartphone tools that can record an electrocardiogram (ECG) strip and make an automated diagnosis overcome these limitations and facilitate timely diagnosis? In the largest study to date, researchers have found that the use of these devices is challenging in patients with abnormal ECGs, although better algorithms and machine learning may help these tools provide more accurate diagnoses.

In the first “real-world” study focusing on the use of the Apple Watch as a diagnostic tool for AF, investigators at the Bordeaux University Hospital (Bordeaux, France) looked at 734 consecutive hospitalized patients. Each patient underwent a 12-lead ECG, immediately followed by a 30-second Apple Watch recording. The smartwatch’s automated single-lead ECG AF detections were classified as “no signs of atrial fibrillation,” “atrial fibrillation,” or “inconclusive reading.” Smartwatch recordings were given to an electrophysiologist who conducted a blinded interpretation, assigning each tracing a diagnosis of “AF,” “absence of AF,” or “diagnosis unclear.” A second blinded electrophysiologist interpreted 100 randomly selected traces to determine the extent to which the observers agreed.

In approximately one in every five patients, the smartwatch ECG failed to produce an automatic diagnosis. The risk of having a false positive automated AF detection was higher for patients with premature atrial and ventricular contractions (PACs/PVCs), sinus node dysfunction, and second- or third-degree atrioventricular-block. For patients in AF, the risk of having a false negative tracing (missed AF) was higher for patients with ventricular conduction abnormalities (interventricular conduction delay) or rhythms controlled by an implanted pacemaker.

The cardiac electrophysiologists had a high level of agreement for differentiation between AF and non-AF. The smartphone app correctly identified 78% of the patients who were in AF and 81% who were not in AF. The electrophysiologists identified 97% of the patients who were in AF and 89% who were not. Patients with PVCs were three times more likely to have false positive AF diagnoses from the smartwatch ECG, and the identification of patients with atrial tachycardia (AT) and atrial flutter (AFL) was very poor.

“These observations are not surprising, as smartwatch automated detection algorithms are based solely on cycle variability,” said lead investigator Marc Strik, MD, PhD, LIRYC institute, Bordeaux University Hospital, Bordeaux, France, explaining that PVCs cause short and long cycles, which increase cycle variability. “Ideally, an algorithm would better discriminate between PVCs and AF. Any algorithm limited to the analysis of cycle variability will have poor accuracy in detecting AT/AFL. Machine learning approaches may increase smartwatch AF detection accuracy in these patients.”

“With the growing use of smartwatches in medicine, it is important to know which medical conditions and ECG abnormalities could impact and alter the detection of AF by the smartwatch in order to optimize the care of our patients,” Dr. Strik added. “Smartwatch detection of AF has great potential, but it is more challenging in patients with pre-existing cardiac disease.”

Related Links:
Bordeaux University Hospital 

BMP Whole Blood Analyzer: GEM Premier ChemSTAT
New
Gold Supplier
Blood Glucose Reference Analyzer
Nova Primary
New
Antimicrobial Susceptibility Testing Software
MICRONAUT6 Software
New
Calcitonin ELISA Test
Calcitonin AccuBind ELISA Test System

Print article
Radcal

Channels

Critical Care

view channel
Image: PATHFAST is a compact immunoanalyzer with superior assay performance (Photo courtesy of PHC Europe)

Benchtop Immunoanalyzer Delivers Lab Quality Results for Cardiology, Intensive Care and Emergency Wards at POC

A compact immunoanalyzer with superior assay performance combines the accuracy of a full-scale lab analyzer with the flexibility of a mobile solution, making it an ideal analysis system for laboratories,... Read more

Surgical Techniques

view channel
Image: Bioelectric medicine could stem excessive blood loss (Photo courtesy of Pexels)

Wearable Neurostimulation Solution Could Stem Excessive Blood Loss in the OR

A wearable neurostimulation solution focused on lessening excessive blood loss could save precious time for surgical teams in the operating room. A collaboration between Spark Biomedical, Inc.... Read more

Patient Care

view channel
Image: The digital stretcher scales are designed specifically for emergent situations in hospitals and emergency rooms (Photo courtesy of DETECTO)

Portable High-Capacity Digital Stretcher Scales Provide Precision Weighing for Patients in ER

For emergency arrivals into a hospital, time is of the essence for gathering patient weights. Now, digital stretcher scales specifically designed for emergent situations in hospitals and emergency rooms... Read more

Health IT

view channel
Image: Using digital data can improve health outcomes (Photo courtesy of Unsplash)

Electronic Health Records May Be Key to Improving Patient Care, Study Finds

When a patient gets transferred from a hospital to a nearby specialist or rehabilitation facility, it is often difficult for personnel at the new facility to access the patient’s electronic health records... Read more

Business

view channel
Image: The global visualization instruments for MIS market is estimated to surpass USD 21 billion by 2031 (Photo courtesy of Pexels)

Global Visualization Instruments for MIS Market Driven by Increasing Demand for Endoscopy Procedures

The last few years have witnessed an increase in patient preference for medical surgeries that involve fewer incisions. As a result, the demand for visualization instruments, which aid in achieving improved... Read more
Copyright © 2000-2022 Globetech Media. All rights reserved.