Modeling Risk Factors and Confounding Effects in Stroke

Abstract

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.

The IMPROVE Guidelines (Ischaemia Models: Procedural Refinements Of in Vivo Experiments)

“…In spite of disagreements on the effects of aging on infarct volume, invariably significantly higher mortality rates and more severe neurological impairments are found in older animals, consistent with clinical data. [74][75][76][77][78] Such detrimental effects, in terms of function and animal welfare, are a direct consequence of the ageing process per se rather than the amount of ischemic damage generated. If the infarct volume is reduced in aged females to that seen in young females by hormone supplementation, the poorer functional ability and increased mortality remain in the aged females.…”

Neuroprotection in Acute Ischemic Stroke: A Battle Against the Biology of Nature

“…Furthermore, some facets of ischemic stroke are not feasible in animal models, including preventative strategies ( 56 ). Although comorbidities such as diabetes and hypertension can be induced into the rodents being tested, the cost is high ( 58 ). Thus, most mice being tested are young and healthy males, although female mice account for a majority of stroke mortalities ( 59 ).…”