24 research outputs found

    Increased hemorrhagic transformation and altered infarct size and localization after experimental stroke in a rat model type 2 diabetes

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    <p>Abstract</p> <p>Background</p> <p>Interruption of flow through of cerebral blood vessels results in acute ischemic stroke. Subsequent breakdown of the blood brain barrier increases cerebral injury by the development of vasogenic edema and secondary hemorrhage known as hemorrhagic transformation (HT). Diabetes is a risk factor for stroke as well as poor outcome of stroke. The current study tested the hypothesis that diabetes-induced changes in the cerebral vasculature increase the risk of HT and augment ischemic injury.</p> <p>Methods</p> <p>Diabetic Goto-Kakizaki (GK) or control rats underwent 3 hours of middle cerebral artery occlusion and 21 h reperfusion followed by evaluation of infarct size, hemorrhage and neurological outcome.</p> <p>Results</p> <p>Infarct size was significantly smaller in GK rats (10 ± 2 vs 30 ± 4%, p < 0.001). There was significantly more frequent hematoma formation in the ischemic hemisphere in GK rats as opposed to controls. Cerebrovascular tortuosity index was increased in the GK model (1.13 ± 0.01 vs 1.34 ± 0.06, P < 0.001) indicative of changes in vessel architecture.</p> <p>Conclusion</p> <p>These findings provide evidence that there is cerebrovascular remodeling in diabetes. While diabetes-induced remodeling appears to prevent infarct expansion, these changes in blood vessels increase the risk for HT possibly exacerbating neurovascular damage due to cerebral ischemia/reperfusion in diabetes.</p

    Comparison of the impact of atrial fibrillation on the risk of early death after stroke in women versus men

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    BACKGROUND: Atrial fibrillation (AF) is considered a predictive factor of poor clinical outcome in patients with an ischemic stroke (IS). This study addressed whether the impact of AF on the in-hospital mortality after first ever IS is different according to the patient’s gender. METHODS: We prospectively studied 1678 patients with first ever IS consecutively admitted to two University Hospitals. We recorded demographic data, vascular risk factors, and the stroke severity (NIHSS) at admission analyzing their impact on the in-hospital mortality and on the combined mortality-dependency at discharge using a Cox proportional hazards model. Two variable interactions between those factors independently related to in-hospital mortality and combined mortality-dependency at discharge were tested. RESULTS: Overall in-hospital mortality was 11.3%. Cox proportional hazards model showed that NIHSS at admission (HR: 1.178 [95% CI 1.149–1.207]), age (HR: 1.044 [95% CI 1.026–1.061]), AF (HR: 1.416 [95% CI 1.048–1.913]), male gender (HR: 1.853 [95% CI 1.323–2.192) and ischemic heart disease (HR: 1.527 [95% CI 1.063–2.192]) were independent predictors of in-hospital mortality. A significant interaction between gender and AF was found (p = 0.017). Data were stratified by gender, showing that AF was an independent predictor of poor outcome just for woman (HR: 2.183 [95% CI 1.403–3.396]; p < 0.001). The independent predictors of combined mortality-disability at discharge were NIHSS at admission (HR: 1.052 [95% CI 1.041–1.063]), age (HR: 1.011 [95% CI 1.004–1.018]), AF (HR: 1.197 [95% CI 1.031–1.390]), ischemic heart disease (HR: 1.222 [95% CI 1.004–1.488]), and smoking (HR: 1.262 [95% CI 1.033–1.541]). CONCLUSIONS: The impact of AF is different in the twogenders and appears as a specific ischemic stroke predictor of in-hospital mortality just for women

    Modeling risk factors and confounding effects in stroke

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