Breakthrough in Mobile Decisions for QT Syndrome-ScienceDaily

The heart is beating by a complex system of electrical signals that causes regular and necessary contractions. Clinicians evaluate the heart’s rate-corrected QT interval (QTc) as an important health barometer of the heart’s electrical charging system. Potentially dangerous long-term QTc of 50 ms or longer can occur due to the following causes:

• Over 100 drugs approved by the Food and Drug Administration (FDA).
• Genetics including congenital long QT syndrome.
• Many systemic diseases, including COVID-19 via SARS-CoV-2.

Such QTc prolongations can make people dangerously fast and chaotic heartbeats, as well as sudden cardiac death. For over 100 years, QTc evaluation and monitoring has relied heavily on 12-lead electrocardiography (EKG). However, according to this study, that could change soon.

Michael Ackerman, MD, Ph.D., a genetic cardiologist at the Mayo Clinic. Under the guidance of, researchers trained and validated AI-based deep neural networks and detected QTc prolongation using AliveCor’s Kardia Mobile 6 LEKG device.Survey results published in circulationIn detecting QT prolongation, we compared the capabilities of AI-enabled mobile EKGs with traditional 12-lead EKGs.

“This collaboration between academia and industry researchers has created what I call the” pivot “discovery,” said Dr. Ackermann, director of the Mayo Clinic’s Windland Smith Rice Comprehensive Sudden Cardiac Death Program. Says. “This pivots from the old method of obtaining the QTc to this new method. Since Eindhoven’s first major EKG treatise in 1903, 2021 marks a new beginning for the QT interval.”

The team used more than 1.6 million 12-lead EKGs from more than 500,000 patients to train and validate AI-based deep neural networks to recognize and accurately measure QTc. Then this newly developed AI-based QTc rating? “QT meter”? It was prospectively tested in nearly 700 patients evaluated by Dr. Ackerman at the Windland Smith Rice Genetic Cardiac Rhythm Clinic at the Mayo Clinic. Half of these patients had congenital long QT syndrome.

The purpose was to compare the QTc values ​​of the 12-lead EKG with the QTc values ​​of the prototype handheld EKG device used in smartphones. Both EKG sets were usually administered within 5 minutes of each other during the same clinical visit.

The ability of AI algorithms to recognize clinically meaningful QTc prolongation on mobile EKG devices is similar to the EKG evaluation performed by trained QT experts and commercial laboratories specializing in QTc measurements in drug studies. did. Mobile devices effectively detect QTc values ​​of 500 ms and above and do the following:

• 80% Sensitivity This means fewer cases of QTc extension.
• 94.4% specificity

This means that the QTc was very accurate in predicting who wasn’t extended.

“The ability to equip mobile EKG devices with an accurate AI-powered approach that can accurately calculate QTc represents a potential paradigm shift in how and where QT intervals are evaluated,” said John Judysessi of Mayo. The doctor of medicine says. Clinic Cardiology Fellow and lead author of research.

“Currently, AliveCor’s Kardia Mobile 6L EKG device is FDA-approved for the detection of atrial fibrillation, bradycardia, and tachycardia. Once FDA-approved for this AI-based QTc assessment, this new vital You get a true QT meter that allows you to sign. You need to get it easily and accurately, “says Dr. Ackerman. “For example, like a diabetics glucose meter, this QT meter provides an early warning system that can identify patients with congenital or acquired LQTS and make life-saving adjustments for drugs and electrolytes. I will. “

“This artificial intelligence point of care application is very scalable because it’s linked to a smartphone. Before taking the first drug, tell people that certain drugs can be harmful. You can save your life, “says Paul. Dr. Friedman, Chairman of the Department of Cardiovascular Medicine, Mayo Clinic, Rochester. “This allows us to detect potentially life-threatening conditions before symptoms appear.”

“Regular monitoring of LQTS using Kardia Mobile 6L enables accurate real-time data collection outside the hospital walls,” said AliveCor Inc. Dr. David Albert, founder and chief healthcare officer of the company, said. The ability to detect this rhythmic abnormality without the 12-lead EKG that requires the patient to be in the hospital improves patient outcomes and hospital resources while providing reliable and timely data to physicians and their patients. Can be saved. “

This study was sponsored by the Mayo Clinic Windland Smith Rice Comprehensive Sudden Cardiac Death Program. Mayo Clinic; Zachi Attia, Ph.D. Peter Noseworthy, MD; Dr. Ackermann; Dr. Friedman, AliveCor, Inc. in connection with this study. Has a financial stake in.

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material Provided by Mayo Clinic.. Original written by Terry Malloy. Note: The content can be edited in style and length.