Clinical Study of Vascular Plaque Determination for Stroke Risk Assessment
Abstract
The high rate of diabetes for the veteran population (~20 percent) tracks with high rates of obesity and these both have increased complications that include carotid stenosis and risk of stroke. Composition information is not available for carotid stenosis even though it is amore import predictor of stroke risk than degree of stenosis. Our hypothesis is that there exist correlations between the information provided by the Compositional Analysis System by Machine learning (CASM) algorithm and future outcomes for patients with carotid artery stenosis. This research effort involves enrolling up to 1500 subjects with significant carotid stenosis at two sites. The asymptomatic patients are followed for up to 3 years in order to determine if there are correlations between future risk of stroke and the output of the CASM algorithm. In addition the output of the CASM algorithm will be analyzed for key populations: e.g. diabetic vs non-diabetic and asymptomatic vs symptomatic. The first subject has been enrolled at each site.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 2021
- Accession Number
- AD1153343
Entities
People
- D. G. Vince
- Michael A. Rosenbaum
- Russell J. Fedewa
- Sheronica L. James