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Avendano, M., Kawachi, I., Van Lenthe, F., Boshuizen, H.C., Mackenbach, J.P., Bos, V., Fay, M.E. and Berkman, L.F. (2006) Socioeconomic Status and Stroke Incidence in the US Elderly: The Role of Risk Factors in the EPESE Study. Stroke, 37, 1368-1373.
https://doi.org/10.1161/01.STR.0000221702.75002.66

has been cited by the following article:

• TITLE: Mathematical Model for Stroke and White Matter Hyperintensities

  AUTHORS: James M. Gregory

  KEYWORDS: Stroke, White Matter Hyperintensities, WMH, Aging, Depression, Trauma, PTSD

  JOURNAL NAME: Journal of Behavioral and Brain Science, Vol.13 No.4, April 30, 2023

  ABSTRACT: A mathematical model was developed to predict the risk of having a stroke as a person ages. The age component was derived from the concept that the change in risk of stroke with age is a function of the current risk of developing a stroke. This equation modeled the trend with age reported in the literature for two different data sets with R2 values of 0.97 or better for both men and women. A second equation of a similar nature was developed to predict the accumulation of white matter hyperintensities, WMH, as a person ages. It appears that each equation includes a set of common risk factors. This set of common risk factors allows an individual’s risk for stroke to be based on measured WMH. A third equation links WMH with the risk of developing a stroke. This equation allows an individual to use measured WMH from brain scans to predict the future risk of developing a stroke. In theory, a person with a relatively high measurement of WMH can project future risk for stroke with age and use counter measures such as exercise and medications to keep other risk factors low as a person continues to age.