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- Arsava, E. M., et al.
(författare)
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The Causative Classification of Stroke system An international reliability and optimization study
- 2010
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Ingår i: Neurology. - 1526-632X. ; 75:14, s. 1277-1284
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Tidskriftsartikel (refereegranskat)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 kappa 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: kappa = 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 kappa 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. Neurology (R) 2010;75:1277-1284
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- Verdelho, A., et al.
(författare)
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White matter changes and diabetes predict cognitive decline in the elderly The LADIS Study
- 2010
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Ingår i: Neurology. - 0028-3878 .- 1526-632X. ; 75:2, s. 160-167
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: We aimed to study if age-related white matter changes (WMC) and vascular risk factors were predictors of cognitive decline in elderly subjects with WMC living independently. METHODS: The Leukoaraiosis and Disability prospective multinational European study (LADIS) evaluates the impact of WMC on the transition of independent elderly subjects into disability. Independent elderly were enrolled due to the presence of WMC. Subjects were evaluated yearly during 3 years with a comprehensive clinical protocol and a neuropsychological battery. Additionally, dementia, subtypes of dementia, and cognitive decline without dementia were classified according to usual clinical criteria. MRI was performed at entry and at the end of the study. RESULTS: A total of 639 subjects were included (74.1 +/- 5 years, 55% women, 9.6 +/- 3.8 years of schooling). At end of follow-up, 90 patients had dementia and 147 had cognitive impairment no dementia. Using Cox regression analysis, WMC severity independently predicted cognitive decline (dementia and not dementia), independently of age, education, and medial temporal atrophy (MTA). Diabetes at baseline was the only vascular risk factor that independently predicted cognitive decline during follow-up, controlling for age, education, WMC severity, and temporal atrophy. Considering subtypes of dementia, Alzheimer disease (AD) was predicted only by MTA, while vascular dementia was predicted by previous stroke, WMC severity, and MTA. CONCLUSION: WMC severity and diabetes are independent predictors of cognitive decline in an initially nondisabled elderly population. Vascular dementia is predicted by previous stroke and WMC, while AD is predicted only by MTA.
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