Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA.
Department of Neurology, Mayo Clinic, Scottsdale, Arizona, USA.
Headache. 2022 Sep;62(8):939-951. doi: 10.1111/head.14339. Epub 2022 Jun 8.
To compare the artificial intelligence-enabled electrocardiogram (AI-ECG) atrial fibrillation (AF) prediction model output in patients with migraine with aura (MwA) and migraine without aura (MwoA).
MwA is associated with an approximately twofold risk of ischemic stroke. Longitudinal cohort studies showed that patients with MwA have a higher incidence of developing AF compared to those with MwoA. The Mayo Clinic Cardiology team developed an AI-ECG algorithm that calculates the probability of concurrent paroxysmal or impending AF in ECGs with normal sinus rhythm (NSR).
Adult patients with an MwA or MwoA diagnosis and at least one NSR ECG within the past 20 years at Mayo Clinic were identified. Patients with an ECG-confirmed diagnosis of AF were excluded. For each patient, the ECG with the highest AF prediction model output was used as the index ECG. Comparisons between MwA and MwoA were conducted in the overall group (including men and women of all ages), women only, and men only in each age range (18 to <35, 35 to <55, 55 to <75, ≥75 years), and adjusted for age, sex, and six common vascular comorbidities that increase risk for AF.
The final analysis of our cross-sectional study included 40,002 patients (17,840 with MwA, 22,162 with MwoA). The mean (SD) age at the index ECG was 48.2 (16.0) years for MwA and 45.9 (15.0) years for MwoA (p < 0.001). The AF prediction model output was significantly higher in the MwA group compared to MwoA (mean [SD] 7.3% [15.0%] vs. 5.6% [12.4%], mean difference [95% CI] 1.7% [1.5%, 2.0%], p < 0.001). After adjusting for vascular comorbidities, the difference between MwA and MwoA remained significant in the overall group (least square means of difference [95% CI] 0.7% [0.4%, 0.9%], p < 0.001), 18 to <35 (0.4% [0.1%, 0.7%], p = 0.022), and 35 to <55 (0.5% [0.2%, 0.8%], p < 0.001), women of all ages (0.6% [0.3%, 0.8%], p < 0.001), men of all ages (1.0% [0.4%, 1.6%], p = 0.002), women 35 to <55 (0.6% [0.3%, 0.9%], p < 0.001), and men 18 to <35 (1.2% [0.3%, 2.1%], p = 0.008).
Utilizing a novel AI-ECG algorithm on a large group of patients, we demonstrated that patients with MwA have a significantly higher AF prediction model output, implying a higher probability of concurrent paroxysmal or impending AF, compared to MwoA in both women and men. Our results suggest that MwA is an independent risk factor for AF, especially in patients <55 years old, and that AF-mediated cardioembolism may play a role in the migraine-stroke association for some patients.
比较伴有先兆偏头痛（MwA）和无先兆偏头痛（MwoA）患者的人工智能心电图（AI-ECG）心房颤动（AF）预测模型输出。
MwA 患者发生缺血性卒中的风险约增加两倍。纵向队列研究显示，与 MwoA 患者相比，MwA 患者发生 AF 的几率更高。Mayo 诊所心脏团队开发了一种 AI-ECG 算法，该算法可计算窦性心律（NSR）心电图中并发阵发性或即将发生 AF 的概率。
在 Mayo 诊所，识别出至少有一次 NSR 心电图且在过去 20 年内诊断为 MwA 或 MwoA 的成年患者。排除心电图确诊为 AF 的患者。对于每位患者，使用 AF 预测模型输出最高的心电图作为索引心电图。在总体人群（包括各年龄段的男性和女性）、仅女性和各年龄段（18 岁至<35 岁、35 岁至<55 岁、55 岁至<75 岁、≥75 岁）的仅男性中，对 MwA 和 MwoA 进行比较，并调整年龄、性别和增加 AF 风险的六种常见血管合并症。
我们的横断面研究的最终分析包括 40002 名患者（17840 名 MwA 患者，22162 名 MwoA 患者）。MwA 组索引心电图的平均（SD）年龄为 48.2（16.0）岁，MwoA 组为 45.9（15.0）岁（p<0.001）。与 MwoA 相比，MwA 组的 AF 预测模型输出明显更高（平均值[SD]7.3%[15.0%]与 5.6%[12.4%]，平均值差异[95%CI]1.7%[1.5%，2.0%]，p<0.001）。调整血管合并症后，总体人群中 MwA 和 MwoA 之间的差异仍然显著（最小二乘均数差值[95%CI]0.7%[0.4%，0.9%]，p<0.001），18 岁至<35 岁（0.4%[0.1%，0.7%]，p=0.022），35 岁至<55 岁（0.5%[0.2%，0.8%]，p<0.001），所有年龄段的女性（0.6%[0.3%，0.8%]，p<0.001），所有年龄段的男性（1.0%[0.4%，1.6%]，p=0.002），35 岁至<55 岁的女性（0.6%[0.3%，0.9%]，p<0.001）和 18 岁至<35 岁的男性（1.2%[0.3%，2.1%]，p=0.008）。
在一大组患者中使用一种新型 AI-ECG 算法，我们证明 MwA 患者的 AF 预测模型输出明显更高，这意味着与 MwoA 相比，女性和男性患者并发阵发性或即将发生 AF 的可能性更高。我们的研究结果表明，MwA 是 AF 的一个独立危险因素，尤其是在<55 岁的患者中，并且 AF 介导的心源性栓塞可能在某些患者的偏头痛-卒中关联中起作用。
