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- Ay, Hakan, et al.
(författare)
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Pathogenic Ischemic Stroke Phenotypes in the NINDS-Stroke Genetics Network
- 2014
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Ingår i: Stroke. - 0039-2499. ; 45:12, s. 3589-3596
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND AND PURPOSE: NINDS (National Institute of Neurological Disorders and Stroke)-SiGN (Stroke Genetics Network) is an international consortium of ischemic stroke studies that aims to generate high-quality phenotype data to identify the genetic basis of pathogenic stroke subtypes. This analysis characterizes the etiopathogenetic basis of ischemic stroke and reliability of stroke classification in the consortium. METHODS: Fifty-two trained and certified adjudicators determined both phenotypic (abnormal test findings categorized in major pathogenic groups without weighting toward the most likely cause) and causative ischemic stroke subtypes in 16954 subjects with imaging-confirmed ischemic stroke from 12 US studies and 11 studies from 8 European countries using the web-based Causative Classification of Stroke System. Classification reliability was assessed with blinded readjudication of 1509 randomly selected cases. RESULTS: The distribution of pathogenic categories varied by study, age, sex, and race (P<0.001 for each). Overall, only 40% to 54% of cases with a given major ischemic stroke pathogenesis (phenotypic subtype) were classified into the same final causative category with high confidence. There was good agreement for both causative (κ 0.72; 95% confidence interval, 0.69-0.75) and phenotypic classifications (κ 0.73; 95% confidence interval, 0.70-0.75). CONCLUSIONS: This study demonstrates that pathogenic subtypes can be determined with good reliability in studies that include investigators with different expertise and background, institutions with different stroke evaluation protocols and geographic location, and patient populations with different epidemiological characteristics. The discordance between phenotypic and causative stroke subtypes highlights the fact that the presence of an abnormality in a patient with stroke does not necessarily mean that it is the cause of stroke.
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| 2. |
- Bots, Michiel L., et al.
(författare)
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Common Carotid Intima-Media Thickness Measurements Do Not Improve Cardiovascular Risk Prediction in Individuals With Elevated Blood Pressure The USE-IMT Collaboration
- 2014
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Ingår i: Hypertension. - 1524-4563. ; 63:6, s. 1173-1181
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Tidskriftsartikel (refereegranskat)abstract
- Carotid intima-media thickness (CIMT) is a marker of cardiovascular risk. It is unclear whether measurement of mean common CIMT improves 10-year risk prediction of first-time myocardial infarction or stroke in individuals with elevated blood pressure. We performed an analysis among individuals with elevated blood pressure (ie, a systolic blood pressure 140 mm Hg and a diastolic blood pressure 90 mm Hg) in USE-IMT, a large ongoing individual participant data meta-analysis. We refitted the risk factors of the Framingham Risk Score on asymptomatic individuals (baseline model) and expanded this model with mean common CIMT (CIMT model) measurements. From both models, 10-year risks to develop a myocardial infarction or stroke were estimated. In individuals with elevated blood pressure, we compared discrimination and calibration of the 2 models and calculated the net reclassification improvement (NRI). We included 17 254 individuals with elevated blood pressure from 16 studies. During a median follow-up of 9.9 years, 2014 first-time myocardial infarctions or strokes occurred. The C-statistics of the baseline and CIMT models were similar (0.73). NRI with the addition of mean common CIMT was small and not significant (1.4%; 95% confidence intervals, -1.1 to 3.7). In those at intermediate risk (n=5008, 10-year absolute risk of 10% to 20%), the NRI was 5.6% (95% confidence intervals, 1.6-10.4). There is no added value of measurement of mean common CIMT in individuals with elevated blood pressure for improving cardiovascular risk prediction. For those at intermediate risk, the addition of mean common CIMT to an existing cardiovascular risk score is small but statistically significant.
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