Abstract
dc:description.abstractStroke risk prediction modeling allows for the identification of individuals who are at heightened stroke risk, which is an important first step in targeted preventive measures. Current stroke risk models are not fully generalizable to multi-ethnic populations because the most widely used one is derived from a predominantly white population, other models are not applicable to both sexes, and the most current model in use is designed to predict global cardiovascular risk and not specific to stroke risk. We have used a Cox proportional hazards regression approach to develop a 10-year stroke risk score in a contemporary multi-ethnic longitudinal cohort that addresses the limitations of the current risk models. This Multi-ethnic Stroke Score adjusts for race/ethnicity and sex, and incorporates traditional cardiovascular risk factors (Age, systolic blood pressure, smoking status, diabetes, and high-density lipoprotein), incident atrial fibrillation, as well as a subclinical marker (coronary artery calcium) of increased stroke risk. Almost all of these risk factors can be easily ascertained in clinical practice and thus can be incorporated into routine clinical assessment.
Degree
thesis:*- Grantor dc:publisher
- Wake Forest University
- Year dc:date.issued
- 2015
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Arnan, Martinson Kweku
Subjects
dc:subject × 1Rights
- Language dc:language.iso
- en
Identifiers
dc:identifier.*- Handle dc:identifier.uri
- http://hdl.handle.net/10339/57153
- OAI identifier oai:identifier
- oai:wakespace.lib.wfu.edu:10339/57153