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      Classification of Stroke Subtypes

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          Abstract

          This article reviews published stroke subtype classification systems and offers rules and a basis for a new way to subtype stroke patients. Stroke subtyping can have different purposes, e.g. describing patients’ characteristics in a clinical trial, grouping patients in an epidemiological study, careful phenotyping of patients in a genetic study, and classifying patients for therapeutic decision-making in daily practice. The classification should distinguish between ischemic and hemorrhagic stroke, subarachnoid hemorrhage, cerebral venous thrombosis, and spinal cord stroke. Regarding the 4 main categories of etiologies of ischemic stroke (i.e. atherothrombotic, small vessel disease, cardioembolic, and other causes), the classification should reflect the most likely etiology without neglecting the vascular conditions that are also found (e.g. evidence of small vessel disease in the presence of severe large vessel obstructions). Phenotypes of large cohorts can also be characterized by surrogate markers or intermediate phenotypes (e.g. presence of internal carotid artery plaque, intima-media thickness of the common carotid artery, leukoaraiosis, microbleeds, or multiple lacunae). Parallel classifications (i.e. surrogate markers) may serve as within-study abnormalities to support research findings.

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          Most cited references 7

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          The Harvard Cooperative Stroke Registry: a prospective registry.

          Data from 694 patients hospitalized with stroke were entered in a prospective, computer-based registry. Three hundred and sixty-four patients (53 percent) were diagnosed as having thrombosis, 215 (31 percent)as having cerebral embolism 70 (10 percent) as having intracerebral hematoma, and 45 (6 percent) as having subarachnoid hemorrhage from aneurysm or arteriovenous malformations. The 364 patients diagnosed as having thrombosis were divided into 233 (34 percent of all 694 patients) whose thrombosis was thought to involve a large artery and 131 (19 percent) with lacunar infarction. Many of the findings in this study were comparable to those in previous registries based on postmortem data. New observations include the high incidence of lacunes and cerebral emboli, the absence of an identifiable cardiac origin in 37 percent of all emboli, a nonsudden onset in 21 percent of emboli, and the occurrence of vomiting at onset in 51 percent and the absence of headache at onset in 67 percent of hematomas.
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            The Lausanne Stroke Registry: analysis of 1,000 consecutive patients with first stroke

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              Improving the reliability of stroke subgroup classification using the Trial of ORG 10172 in Acute Stroke Treatment (TOAST) criteria.

              We sought to improve the reliability of the Trial of ORG 10172 in Acute Stroke Treatment (TOAST) classification of stroke subtype for retrospective use in clinical, health services, and quality of care outcome studies. The TOAST investigators devised a series of 11 definitions to classify patients with ischemic stroke into 5 major etiologic/pathophysiological groupings. Interrater agreement was reported to be substantial in a series of patients who were independently assessed by pairs of physicians. However, the investigators cautioned that disagreements in subtype assignment remain despite the use of these explicit criteria and that trials should include measures to ensure the most uniform diagnosis possible. In preparation for a study of outcomes and management practices for patients with ischemic stroke within Department of Veterans Affairs hospitals, 2 neurologists and 2 internists first retrospectively classified a series of 14 randomly selected stroke patients on the basis of the TOAST definitions to provide a baseline assessment of interrater agreement. A 2-phase process was then used to improve the reliability of subtype assignment. In the first phase, a computerized algorithm was developed to assign the TOAST diagnostic category. The reliability of the computerized algorithm was tested with a series of synthetic cases designed to provide data fitting each of the 11 definitions. In the second phase, critical disagreements in the data abstraction process were identified and remaining variability was reduced by the development of standardized procedures for retrieving relevant information from the medical record. The 4 physicians agreed in subtype diagnosis for only 2 of the 14 baseline cases (14%) using all 11 TOAST definitions and for 4 of the 14 cases (29%) when the classifications were collapsed into the 5 major etiologic/pathophysiological groupings (kappa=0.42; 95% CI, 0.32 to 0.53). There was 100% agreement between classifications generated by the computerized algorithm and the intended diagnostic groups for the 11 synthetic cases. The algorithm was then applied to the original 14 cases, and the diagnostic categorization was compared with each of the 4 physicians' baseline assignments. For the 5 collapsed subtypes, the algorithm-based and physician-assigned diagnoses disagreed for 29% to 50% of the cases, reflecting variation in the abstracted data and/or its interpretation. The use of an operations manual designed to guide data abstraction improved the reliability subtype assignment (kappa=0.54; 95% CI, 0.26 to 0.82). Critical disagreements in the abstracted data were identified, and the manual was revised accordingly. Reliability with the use of the 5 collapsed groupings then improved for both interrater (kappa=0.68; 95% CI, 0.44 to 0.91) and intrarater (kappa=0.74; 95% CI, 0.61 to 0.87) agreement. Examining each remaining disagreement revealed that half were due to ambiguities in the medical record and half were related to otherwise unexplained errors in data abstraction. Ischemic stroke subtype based on published TOAST classification criteria can be reliably assigned with the use of a computerized algorithm with data obtained through standardized medical record abstraction procedures. Some variability in stroke subtype classification will remain because of inconsistencies in the medical record and errors in data abstraction. This residual variability can be addressed by having 2 raters classify each case and then identifying and resolving the reason(s) for the disagreement.
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                Author and article information

                Journal
                CED
                Cerebrovasc Dis
                10.1159/issn.1015-9770
                Cerebrovascular Diseases
                S. Karger AG
                1015-9770
                1421-9786
                2009
                April 2009
                03 April 2009
                : 27
                : 5
                : 493-501
                Affiliations
                aDepartment of Neurology and Stroke Center, INSERM U-698 and Paris-Diderot University, Bichat University Hospital, Paris, France; bDepartment of Neurology, Genolier Swiss Medical Network, Valmont-Genolier, Glion-sur-Montreux, Switzerland; cDivision of Cerebrovascular/Stroke, Beth Israel Deaconess Medical Center, Boston, Mass., USA; dNational Stroke Research Institute, Austin Health, University of Melbourne, Melbourne, Vic., Australia; eDepartment of Neurology, University of Heidelberg, Universitätsklinikum Mannheim, Mannheim, Germany
                Article
                210432 Cerebrovasc Dis 2009;27:493–501
                10.1159/000210432
                19342825
                a16db4a2-20e9-49c8-9fe2-6dc6ae4a6235
                © 2009 S. Karger AG, Basel

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                Page count
                Tables: 3, References: 13, Pages: 9
                Categories
                Original Paper

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