Department of Neurology, Eulji University Hospital, Eulji University, Daejeon, Korea.
Department of Neurology, Cerebrovascular Center, Seoul National University Bundang Hospital, Seongnam, Korea.
J Stroke. 2014 Sep;16(3):161-72. doi: 10.5853/jos.2014.16.3.161. Epub 2014 Sep 30.
In order to improve inter-rater reliability and minimize diagnosis of undetermined etiology for stroke subtype classification, using a stroke registry, we developed and implemented a magnetic resonance imaging (MRI)-based algorithm for acute ischemic stroke subtype classification (MAGIC).
We enrolled patients who experienced an acute ischemic stroke, were hospitalized in the 14 participating centers within 7 days of onset, and had relevant lesions on MR-diffusion weighted imaging (DWI). MAGIC was designed to reflect recent advances in stroke imaging and thrombolytic therapy. The inter-rater reliability was compared with and without MAGIC to classify the Trial of Org 10172 in Acute Stroke Treatment (TOAST) of each stroke patient. MAGIC was then applied to all stroke patients hospitalized since July 2011, and information about stroke subtypes, other clinical characteristics, and stroke recurrence was collected via a web-based registry database.
The overall intra-class correlation coefficient (ICC) value was 0.43 (95% CI, 0.31-0.57) for MAGIC and 0.28 (95% CI, 0.18-0.42) for TOAST. Large artery atherosclerosis (LAA) was the most common cause of acute ischemic stroke (38.3%), followed by cardioembolism (CE, 22.8%), undetermined cause (UD, 22.2%), and small-vessel occlusion (SVO, 14.6%). One-year stroke recurrence rates were the highest for two or more UDs (11.80%), followed by LAA (7.30%), CE (5.60%), and SVO (2.50%).
Despite several limitations, this study shows that the MAGIC system is feasible and may be helpful to classify stroke subtype in the clinic.
为了提高对卒中亚型分类的观察者间信度，减少对病因不明的卒中的诊断，我们基于卒中登记系统，开发并实施了一种基于磁共振成像（MRI）的急性缺血性卒中亚型分类算法（MAGIC）。
我们纳入了发病后 7 天内于 14 个参与中心住院且弥散加权成像（DWI）有相关病灶的急性缺血性卒中患者。MAGIC 旨在反映卒中影像学和溶栓治疗的最新进展。通过比较有无 MAGIC 对每位卒中患者进行的试验性组织型纤溶酶原激活剂治疗急性卒中（TOAST）分类，评估其观察者间信度。然后，我们将 MAGIC 应用于自 2011 年 7 月以来住院的所有卒中患者，并通过基于网络的登记数据库收集卒中亚型、其他临床特征和卒中复发的信息。
MAGIC 的总体组内相关系数（ICC）值为 0.43（95%可信区间，0.310.57），TOAST 为 0.28（95%可信区间，0.180.42）。大动脉粥样硬化（LAA）是急性缺血性卒中最常见的病因（38.3%），其次是心源性栓塞（CE，22.8%）、病因不明（UD，22.2%）和小血管闭塞（SVO，14.6%）。两种或两种以上 UD 的 1 年卒中复发率最高（11.80%），其次是 LAA（7.30%）、CE（5.60%）和 SVO（2.50%）。
尽管存在一些局限性，但本研究表明 MAGIC 系统是可行的，并且可能有助于在临床中对卒中亚型进行分类。
