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AHS 2022 | AI-ECG atrial fibrillation prediction model in migraine with and without aura

Chia-Chun Chiang, MD, Mayo Clinic, Rochester, MN, discusses the use of a novel artificial intelligence-enabled ECG (AI-ECG) atrial fibrillation (AF) prediction model in patients with migraine with aura (MwA) and migraine without aura. It is known that MwA is associated with a higher risk of ischemic stroke compared to migraine without aura – longitudinal studies also suggest that MwA is associated with AF, presenting a significant risk factor for cardioembolic stroke. This led to Dr Chiang’s study concerning the association between AF and migraine utilizing a novel AI-ECG algorithm to determine the probability of subclinical or undetected AF. The algorithm was applied to study and compare all ECGs in MwA to patients without aura – thus, retrospectively collating all patients with a migraine diagnosis between 2000 and 2020. All the ECG information was extracted and implemented under the AI-ECG AF prediction model output. Due to wanting to study the probability of subclinical AF, all patients diagnosed with AF were excluded from the study. Furthermore, the inclusion criterium was also adjusted for age, sex, and vascular risk factors – finding that patients with MwA had a significantly higher AI-ECG atrial fibrillation model output when compared to those without aura. This interview took place during the 2022 American Headache Society (AHS) Meeting in Denver, CO.