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1.
Acta Neurol Scand ; 126(5): 329-35, 2012 Nov.
Article in English | MEDLINE | ID: mdl-22339042

ABSTRACT

OBJECTIVES: There are few studies on long-term outcome after ischemic stroke (IS) for young and middle-aged stroke sufferers in relation to etiologic subtypes. Here, we report 2-year outcome in the Sahlgrenska Academy Study on Ischemic Stroke (SAHLSIS). MATERIALS AND METHODS: SAHLSIS comprises 600 patients with IS before the age of 70 years. Etiologic subtype of IS was classified according to Trial of Org 10172 in Acute Stroke Treatment (TOAST). Recurrent vascular events and death were registered using several overlapping methods. Functional outcome was assessed according to the modified Rankin Scale (mRS). RESULTS: After 2 years, 55 (9.2%) patients had suffered a recurrent stroke, 15 (2.5%) had a transient ischemic attack (TIA), 4 (0.7%) had a coronary event, and 24 (4.0%) had died. The number of recurrent stroke, TIA, and death differed significantly between etiologic stroke subtypes. The highest rates were observed in large-vessel disease (LVD), whereas small-vessel disease and cryptogenic stroke showed the lowest recurrence and mortality rates. LVD was a significant predictor of the composite outcome (recurrent stroke, TIA, coronary event and/or death) independently of cardiovascular risk factors and stroke severity. Stroke subtype also predicted functional outcome 2 years after index stroke, but this association was not retained after adjustment for stroke severity. CONCLUSIONS: In young and middle-aged stroke patients, stroke subtype predicts recurrent vascular events and/or death 2 years after index stroke independently of cardiovascular risk factors and stroke severity. Thus, it is important to take the etiologic subtype of IS in account when assessing the risk of recurrence both in the clinical setting and in future studies.


Subject(s)
Stroke/etiology , Adult , Female , Follow-Up Studies , Humans , Ischemic Attack, Transient/epidemiology , Kaplan-Meier Estimate , Male , Middle Aged , Recovery of Function , Recurrence , Risk Factors , Stroke/mortality , Stroke/physiopathology , Treatment Outcome
3.
Neurology ; 75(14): 1277-84, 2010 Oct 05.
Article in English | MEDLINE | ID: mdl-20921513

ABSTRACT

BACKGROUND: Valid and reliable ischemic stroke subtype determination is crucial for well-powered multicenter studies. The Causative Classification of Stroke System (CCS, available at http://ccs.mgh.harvard.edu) is a computerized, evidence-based algorithm that provides both causative and phenotypic stroke subtypes in a rule-based manner. We determined whether CCS demonstrates high interrater reliability in order to be useful for international multicenter studies. METHODS: Twenty members of the International Stroke Genetics Consortium from 13 centers in 8 countries, who were not involved in the design and development of the CCS, independently assessed the same 50 consecutive patients with acute ischemic stroke through reviews of abstracted case summaries. Agreement among ratings was measured by kappa statistic. RESULTS: The κ value for causative classification was 0.80 (95% confidence interval [CI] 0.78-0.81) for the 5-subtype, 0.79 (95% CI 0.77-0.80) for the 8-subtype, and 0.70 (95% CI 0.69-0.71) for the 16-subtype CCS. Correction of a software-related factor that generated ambiguity improved agreement: κ = 0.81 (95% CI 0.79-0.82) for the 5-subtype, 0.79 (95% CI 0.77-0.80) for the 8-subtype, and 0.79 (95% CI 0.78-0.80) for the 16-subtype CCS. The κ value for phenotypic classification was 0.79 (95% CI 0.77-0.82) for supra-aortic large artery atherosclerosis, 0.95 (95% CI 0.93-0.98) for cardioembolism, 0.88 (95% CI 0.85-0.91) for small artery occlusion, and 0.79 (0.76-0.82) for other uncommon causes. CONCLUSIONS: CCS allows classification of stroke subtypes by multiple investigators with high reliability, supporting its potential for improving stroke classification in multicenter studies and ensuring accurate means of communication among different researchers, institutions, and eras.


Subject(s)
Causality , International Cooperation , Stroke/classification , Stroke/diagnosis , Cardiovascular Diseases/complications , Data Collection , Female , Humans , Male , Reproducibility of Results , Risk Factors , Stroke/etiology
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