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.
- 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.