Modeling Risk Factors and Confounding Effects in Stroke
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Most research to date has used experimental models in rodents which fail to mimic the underlying causes of stroke in patients or the primary confounding factors. Available data indicate that factors such as atherosclerosis, hypertension, obesity, diabetes, age, and inflammation have a major influence on outcome. These findings suggest that we need to rethink the preclinical data that are required before selection of candidate interventions for clinical trials in stroke.
