Sobrino García P, García Pastor A, García Arratibel A, Vicente Peracho G, Rodriguez Cruz P M, Pérez Sánchez J R, Díaz Otero F, Vázquez Alén P, Villanueva Osorio J A, Gil Núñez A
Unidad de Ictus, Servicio de Neurología, Hospital General Universitario Gregorio Marañón, Madrid, España.
Neurologia. 2013 Sep;28(7):417-24. doi: 10.1016/j.nrl.2012.07.005. Epub 2012 Sep 19.
The A-S-C-O classification may be better than other methods for classifying ischaemic stroke by aetiology. Our aims are to describe A-S-C-O phenotype distribution (A: atherosclerosis, S: small vessel disease, C: cardiac source, O: other causes; 1: potential cause, 2: causality uncertain, 3: unlikely to be a direct cause although disease is present) and compare them to the Spanish Society of Neurology's Cerebrovascular Disease Study Group (GEECV/SEN) classification. We will also find the degree of concordance between these classification methods and determine whether using the A-S-C-O classification delivers a smaller percentage of strokes of undetermined cause.
We analysed those patients with ischaemic stroke admitted to our stroke unit in 2010 with strokes that were classified according to GEECV/SEN and A-S-C-O criteria.
The study included 496 patients. The percentages of strokes caused by atherosclerosis and small vessel disease according to GEECV/SEN criteria were higher than the percentages for potential atherosclerotic stroke (A1) (14.1 vs. 11.9%; P=.16) and potential small vessel stroke (S1) (14.3 vs. 3%; P<.001). Cardioembolic stroke (C1) was more frequent (22.2 vs. 31%; P<.001). No differences between unusual cause of stroke and other potential causes (O1) were observed. Some degree of atherosclerosis was present in 53.5% of patients (A1, A2, or A3); 65.5% showed markers of small vessel disease (S1, S2, or S3), and 74.9% showed signs of cardioembolism (C1, C2, or C3). Fewer patients in the group without scores of 1 or 2 for any of the A-S-C-O phenotypes were identified as having a stroke of undetermined cause (46.6 vs. 29.2%; P<.001). The agreement between the 2 classifications ranged from κ<0.2 (small vessel and S1) to κ>0.8 (unusual causes and O1).
Our results show that GEECV/SEN and A-S-C-O classifications are neither fully comparable nor consistent. Using the A-S-C-O classification provided additional information on co-morbidities and delivered a smaller percentage of strokes classified as having an undetermined cause.
A-S-C-O分类法在按病因对缺血性中风进行分类方面可能优于其他方法。我们的目的是描述A-S-C-O表型分布（A：动脉粥样硬化，S：小血管疾病，C：心源，O：其他原因；1：潜在病因，2：因果关系不确定，3：尽管存在疾病但不太可能是直接病因），并将其与西班牙神经病学学会脑血管疾病研究组（GEECV/SEN）的分类法进行比较。我们还将找出这些分类方法之间的一致程度，并确定使用A-S-C-O分类法是否能降低病因未明的中风所占比例。
我们分析了2010年入住我院卒中单元的缺血性中风患者，这些中风根据GEECV/SEN和A-S-C-O标准进行分类。
该研究纳入了496例患者。根据GEECV/SEN标准，由动脉粥样硬化和小血管疾病引起的中风百分比高于潜在动脉粥样硬化性中风（A1）（14.1%对11.9%；P = 0.16）和潜在小血管中风（S1）（14.3%对3%；P<0.001）的百分比。心源性栓塞性中风（C1）更为常见（22.2%对31%；P<0.001）。未观察到中风的不寻常病因与其他潜在病因（O1）之间存在差异。53.5%的患者存在某种程度的动脉粥样硬化（A1、A2或A3）；65.5%的患者有小血管疾病标志物（S1、S2或S3），74.9%的患者有心脏栓塞迹象（C1、C2或C3）。在A-S-C-O任何表型得分均不为1或2的组中，被确定为病因未明的中风患者较少（46.6%对29.2%；P<0.001）。两种分类之间的一致性范围从κ<0.2（小血管与S1）到κ>0.8（不寻常病因与O1）。
我们的结果表明，GEECV/SEN和A-S-C-O分类法既不完全可比也不一致。使用A-S-C-O分类法可提供有关合并症的额外信息，并降低分类为病因未明的中风所占比例。
