Currently Viewing:
American Heart Association Scientific Sessions 2019
Kiersten Combs Discusses Findings of the DAPA-HF Study in Population Without Diabetes
November 17, 2019
Dr Jay Edelberg Outlines the Clinical Burdens and Treatment Options for Hypertrophic Cardiomyopathy
November 17, 2019
Details of DAPA-HF Results Point to Dapagliflozin for Some Heart Failure Patients Without Diabetes
November 17, 2019
In Stable Heart Disease, Study Finds Stents Might Be No Better Than Drugs
November 17, 2019
Dapagliflozin Meets Quality-of-Life Marks, Efficacy Among Seniors, Data Show
November 17, 2019
From Self-Reporting Accuracy to Therapy Access: AHA Posters Cover Issues in Disparities
November 18, 2019
Currently Reading
Dr John Pfeifer Outlines Necessary Steps for Preventive Action in Patients With Atrial Fibrillation
November 18, 2019
Plaques May Be Key to Vascepa's Role in Preventing CV Events
November 18, 2019
48-Week Results for Mavacamten Draw Crowd at AHA Session
November 19, 2019
Dr Vinay Kini Discusses the Growing Influence of the EHR in the Transition to Value-Based Care
November 19, 2019
Dr Stephen Heitner Details the Significance of the PIONEER-OLE Study in Treating Obstructive HCM
November 19, 2019
Dr Stephen Heitner Outlines the Next Steps After MAVERICK-HCM Study Findings
November 21, 2019
Dr Stephen Voyce Details Innovations and Preventive Strategies in Detection of Atrial Fibrillation
November 24, 2019
Dr Brent Williams Discusses Study Findings on Detection of Atrial Fibrillation
November 27, 2019
Dr Brandon Fornwalt Discusses the Preventive Efficacy of AI in Monitoring for Atrial Fibrillation
November 30, 2019
Dr Douglas Losordo Discusses the Evolution and Importance of CD34+ Treatment in Patients With CMD
December 04, 2019
Dr Brian Ghoshhajra Details the Significance of the PDS-2 System in Affecting Progression of HoFH
December 05, 2019
Dr Roland Chen Outlines the GUARD-AF Trial as a Preventive Mechanism in Reducing Risk of Stroke
December 06, 2019
Dr Darryl Sleep: Identifying and Treating Elevated LDL-C in Patients Can Mitigate Heart Attack Risk
December 06, 2019

Dr John Pfeifer Outlines Necessary Steps for Preventive Action in Patients With Atrial Fibrillation

By identifying patients at very high risk for atrial fibrillation, preventive measures and screening strategies can be implemented for heightened patient care, said John Pfeifer, MD, MPH, cardiologist at Geisinger Medical Center.


By identifying patients at very high risk for atrial fibrillation, preventive measures and screening strategies can be implemented for heightened patient care, said John Pfeifer, MD, MPH, cardiologist at Geisinger Medical Center.

Transcript

Based on the study results showing that artificial intelligence (AI) predicted incident atrial fibrillation directly from electrocardiogram traces, can you discuss the significance of a deep neural network as an accurate predictor for preventive treatment of atrial fibrillation?

Atrial fibrillation is the most common abnormal heart rhythm. Some studies suggest that up to 1 in 3 people will develop atrial fibrillation at some point in their life. This is important because atrial fibrillation is associated with a number of bad outcomes–chief amongst them being stroke. Strokes can obviously be devastating–they can lead to death, they can lead to loss of function ability, permanent residence in a nursing home. So, we have a great interest in preventing strokes if we can. Now 1 of the tricky things about atrial fibrillation is it is often asymptomatic; patients do not know they have it. Even in those asymptomatic patients, they are still at risk for stroke. We know that we can reduce the risk of stroke in atrial fibrillation, but that requires medicines called anticoagulants. Those medications have risk associated with them, primarily bleeding. So, we don’t want to give them out indiscriminately–we need an accurate diagnosis of atrial fibrillation before we prescribe the anticoagulant. This is where our model really comes in.

People have been interested in screening atrial fibrillation for a long time, but we’ve not really figured out the right way to do it. Now, part of the problem is that even though the prevalence of atrial fibrillation increases as people age, the year-to-year incidence remains pretty low in most age groups. So, any screening strategy needs to take that into account. Furthermore, the other thing that makes atrial fibrillation really difficult is the fact that it’s often paroxysmal. People can have episodes that are relatively short-lived but still increase the risk of stroke. So, the question then becomes, how do we capture those patients? There’s lots of different monitoring strategies out there–we can check a patient’s pulse when they come for the doctor’s visit, we can do an EKG at a single point in time. More sophisticated strategies look at patches or monitors that people wear continuously for 2 to 3 weeks at a time. We even have devices that can implanted in the body which can stand for over a year for long-term monitoring of atrial fibrillation.

Now, the problem with any of those strategies is 1, they are costly–2, in implantable monitors and invasive procedures, although the risk is small, there is some risk associated with putting them in. So, 1 of the things that we want to do is identify the very high-risk populations and then target our screening strategies around them and that is exactly where our model comes into play. We identify the patients that are very high risk for the development of atrial fibrillation within the next 1 year. Now at that point, there are a number of screening strategies that we can employ in that population to try to find the afib [atrial fibrillation], prevent the stroke.

 
Copyright AJMC 2006-2019 Clinical Care Targeted Communications Group, LLC. All Rights Reserved.
x
Welcome the the new and improved AJMC.com, the premier managed market network. Tell us about yourself so that we can serve you better.
Sign Up