A Role for AI-enabled ECG in Cryptogenic Stroke?

Approximately 20% of all ischemic strokes are cryptogenic. In other words, they have an uncertain cause despite thorough diagnostic evaluation. Many of these patients undergo long-term cardiac monitoring for detection of atrial fibrillation (AF), but in the absence of clearly documented AF, there is controversy regarding the best approach to secondary prevention. While anticoagulation may seem reasonable for some patients, empiric anticoagulation has not been shown to prevent recurrent events and may not outweigh the risk of bleeding in patients with embolic stroke of unknown source (ie, cryptogenic strokes with embolic pattern on brain imaging but no documented embolic source).

We recently reported on the application of artificial intelligence to the electrocardiogram (artificial intelligence–enabled electrocardiogram; AI-ECG) to identify patients who may have a particularly high likelihood of concomitant AF or atrial flutter, even though their presenting rhythm was sinus. In our recent work in HeartRhythm Case Reports, we present a case of a patient with recurrent cryptogenic stroke in whom repeat ECGs and cardiac monitoring recorded sinus rhythm, but retrospective AI-ECG analysis demonstrated forewarning of AF risk 12 years prior to the first thromboembolic event.

Reference: Kashou AH, Rabinstein AA, Attia IZ, Gersh BJ, Freidman PA, Noseworthy PA. Recurrent cryptogenic stroke: A potential role for an artificial intelligence-enabled electrocardiogram? HeartRhythm Case Reports. 6;4:202-205. 2020.

Read the full article here.

Key Takeaways

• Many patients with cryptogenic stroke are suspected to have underlying paroxysmal atrial fibrillation (AF). However, in the absence of proven AF, anticoagulation of these patients has not been shown to prevent recurrent ischemic strokes and may result in excess bleeding compared with aspirin.
• The artificial intelligence–enabled electrocardiogram (AI-ECG) may identify patients with a particularly high likelihood of concomitant AF in the setting of sinus rhythm.
• AI-ECG may serve as an AF/atrial myopathy risk marker and could influence management of patients with cryptogenic stroke. Further study will be required to evaluate and validate the clinical utility of AI-ECG in patient care.