Ryoo Sookyung, Chung Jong-Won, Lee Mi Ji, Kim Suk Jae, Lee Jin Soo, Kim Gyeong-Moon, Chung Chin-Sang, Lee Kwang Ho, Hong Ji Man, Bang Oh Young
Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
Department of Neurology, Ajou University Hospital, Ajou University School of Medicine, Suwon, South Korea.
J Am Heart Assoc. 2016 Mar 22;5(3):e002975. doi: 10.1161/JAHA.115.002975.
From a therapeutic viewpoint, it is important to differentiate the underlying causes of embolism in patients with cryptogenic stroke, such as aortic arch atheroma, patent foramen ovale, and paroxysmal atrial fibrillation. We investigated the clinical and radiological characteristics of these 3 common causes of cryptogenic embolism to develop models for decision making in etiologic workups.
A total of 321 consecutive patients with acute infarcts from cryptogenic embolism were included. Patients were divided into 3 groups-aortic arch atheroma (n=40), patent foramen ovale (n=153), and paroxysmal atrial fibrillation (n=128)-based on extensive cardiologic workups. We used a multinomial logistic regression analysis to detect the clinical and diffusion-weighted imaging factors associated with the probability of aortic arch atheroma, patent foramen ovale, and paroxysmal atrial fibrillation. Clinical and radiological features differed among the groups. The patent foramen ovale group had a healthy vascular risk factor profile and showed posterior circulation involvement compared with other groups (P<0.01). In contrast, paroxysmal atrial fibrillation-related strokes had higher initial National Institutes of Health Stroke Scale (NIHSS) scores and larger lesions than the other groups (P<0.001). The aortic arch atheroma group had clinical features similar to those of the paroxysmal atrial fibrillation group but showed small lesions scattered in multiple vascular territories (P<0.001). Multivariate regression analysis revealed that age, initial NIHSS score, lesion size (≥20 mm), multiple (≥3) lesions, and involvement of posterior circulation or multiple vascular territories differentiated the 3 groups (pseudo, R(2)=0.656). The prediction ability of this model was validated in the external validation cohort (n=117, area under the curve 0.78).
Our data indicate that patients with cryptogenic embolic stroke show distinct clinical and radiological features depending on the underlying causes.
从治疗角度来看，区分不明原因卒中患者栓塞的潜在病因非常重要，如主动脉弓动脉粥样硬化、卵圆孔未闭和阵发性心房颤动。我们研究了这3种不明原因栓塞的常见病因的临床和影像学特征，以建立病因检查中的决策模型。
共纳入321例连续的不明原因栓塞所致急性梗死患者。根据广泛的心脏检查，将患者分为3组——主动脉弓动脉粥样硬化组（n = 40）、卵圆孔未闭组（n = 153）和阵发性心房颤动组（n = 128）。我们使用多项逻辑回归分析来检测与主动脉弓动脉粥样硬化、卵圆孔未闭和阵发性心房颤动可能性相关的临床和弥散加权成像因素。各组的临床和影像学特征有所不同。与其他组相比，卵圆孔未闭组具有健康的血管危险因素特征，且后循环受累（P<0.01）。相比之下，阵发性心房颤动相关卒中的初始美国国立卫生研究院卒中量表（NIHSS）评分更高，病变更大（P<0.001）。主动脉弓动脉粥样硬化组的临床特征与阵发性心房颤动组相似，但病变较小，散在于多个血管区域（P<0.001）。多变量回归分析显示，年龄、初始NIHSS评分、病变大小（≥20 mm）、多个（≥3个）病变以及后循环或多个血管区域受累可区分这3组（伪R(2)=0.656）。该模型的预测能力在外部验证队列（n = 117，曲线下面积0.78）中得到验证。
我们的数据表明，不明原因栓塞性卒中患者根据潜在病因表现出不同的临床和影像学特征。
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