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      Chinese Ischemic Stroke Subclassification

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          Abstract

          Accurate classification of stroke has significant impact on patient care and conduction of stroke clinical trials. The current systems such as TOAST, SSS-TOAST, Korean TOAST, and A–S–C–O have limitations. With the advent of new imaging technology, there is a need to have a more accurate stroke subclassification system. Chinese ischemic stroke subclassification (CISS) system is a new two step system aims at the etiology and then underlying mechanism of a stroke. The first step classify stroke into five categories: large artery atherosclerosis (LAA), including atherosclerosis of aortic arch and intra-/extracranial large arteries, cardiogenic stroke, penetrating artery disease, other etiology, and undetermined etiology. The second step is to further classify the underlying mechanism of ischemic stroke from the intracranial and extracranial LAA into the parent artery (plaque or thrombosis) occluding penetrating artery, artery-to-artery embolism, hypoperfusion/impaired emboli clearance, and multiple mechanisms. Although clinical validation of CISS is being planned, CISS is an innovative system that offers much more detailed information on the pathophysiology of a stroke.

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          Most cited references19

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          Intracranial branch atheromatous disease: a neglected, understudied, and underused concept.

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            A computerized algorithm for etiologic classification of ischemic stroke: the Causative Classification of Stroke System.

            The SSS-TOAST is an evidence-based classification algorithm for acute ischemic stroke designed to determine the most likely etiology in the presence of multiple competing mechanisms. In this article, we present an automated version of the SSS-TOAST, the Causative Classification System (CCS), to facilitate its utility in multicenter settings. The CCS is a web-based system that consists of questionnaire-style classification scheme for ischemic stroke (http://ccs.martinos.org). Data entry is provided via checkboxes indicating results of clinical and diagnostic evaluations. The automated algorithm reports the stroke subtype and a description of the classification rationale. We evaluated the reliability of the system via assessment of 50 consecutive patients with ischemic stroke by 5 neurologists from 4 academic stroke centers. The kappa value for inter-examiner agreement was 0.86 (95% CI, 0.81 to 0.91) for the 5-item CCS (large artery atherosclerosis, cardio-aortic embolism, small artery occlusion, other causes, and undetermined causes), 0.85 (95% CI, 0.80 to 0.89) with the undetermined group broken into cryptogenic embolism, other cryptogenic, incomplete evaluation, and unclassified groups (8-item CCS), and 0.80 (95% CI, 0.76 to 0.83) for a 16-item breakdown in which diagnoses were stratified by the level of confidence. The intra-examiner reliability was 0.90 (0.75-1.00) for 5-item, 0.87 (0.73-1.00) for 8-item, and 0.86 (0.75-0.97) for 16-item CCS subtypes. The web-based CCS allows rapid analysis of patient data with excellent intra- and inter-examiner reliability, suggesting a potential utility in improving the fidelity of stroke classification in multicenter trials or research databases in which accurate subtyping is critical.
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              LACUNES: SMALL, DEEP CEREBRAL INFARCTS.

              C M Fisher (1965)
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                Author and article information

                Journal
                Front Neurol
                Front. Neur.
                Frontiers in Neurology
                Frontiers Research Foundation
                1664-2295
                15 February 2011
                2011
                : 2
                : 6
                Affiliations
                [1] 1simpleDepartment of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College Beijing, China
                [2] 2simpleDepartment of Neurology, Beijing Tiantan Hospital, Capital Medical University Beijing, China
                [3] 3simpleDepartment of Neurology, The First Affiliated Hospital of Jinan University Guangzhou, China
                [4] 4simpleDepartment of Neurology, Renji Hospital, Shanghai Jiaotong University School of Medicine Shanghai, China
                [5] 5simpleIllinois Neurological Institute Stroke Network, OSF Healthcare Systems, Department of Neurology, University of Illinois College of Medicine at Peoria Peoria, IL, USA
                Author notes

                Edited by: David S. Liebeskind, University of California Los Angeles, USA

                Reviewed by: Jose G. Merino, Suburban Hospital, USA; Nerses Sanossian, University of Southern California, USA; Wengui Yu, University of Texas Southwestern Medical Center at Dallas, USA

                *Correspondence: Y. J. Wang, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100053, China. e-mail: yongjunwang111@ 123456yahoo.com.cn

                This article was submitted to Frontiers in Stroke, a specialty of Frontiers in Neurology.

                Article
                10.3389/fneur.2011.00006
                3052771
                21427797
                4081017d-e010-43d0-8bdc-e9103630cfb5
                Copyright © 2011 Gao, Wang, Xu, Li and Wang.

                This is an open-access article subject to an exclusive license agreement between the authors and Frontiers Media SA, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are credited.

                History
                : 02 October 2010
                : 31 January 2011
                Page count
                Figures: 3, Tables: 0, Equations: 0, References: 24, Pages: 5, Words: 3633
                Categories
                Neuroscience
                Hypothesis and Theory

                Neurology
                subclassification,ischemic stroke,mechanism,etiology,chinese
                Neurology
                subclassification, ischemic stroke, mechanism, etiology, chinese

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