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Author Spotlight: Assessing Ischemic Stroke Damage Through Middle Cerebral Artery Occlusion Model
Published on: August 11, 2023
Self-Reported Stroke Risk Stratification: Reasons for Geographic and Racial Differences in Stroke Study
George Howard1, Leslie A McClure2, Claudia S Moy2
1From the Departments of Biostatistics (G.H., S.E.J., Y.Y., D.L.L.) and Epidemiology (V.J.H., P.M.), School of Public Health, University of Alabama at Birmingham; Department of Biostatistics and Epidemiology, Drexel University, Philadelphia, PA (L.A.M.); National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD (C.S.M.); Division of General Internal Medicine, Cornell School of Medicine, New York, NY (M.M.S.); and Department of Neurology, University of Cincinnati, OH (D.O.K.). ghoward@uab.edu.
A new self-reported stroke risk function (SRSRF) identifies individuals at high risk for stroke more effectively than the established Framingham Stroke Risk Function (FSRF). This simple questionnaire improves stroke risk prediction and clinical identification of at-risk populations.
Area of Science:
- Cardiovascular epidemiology
- Public health
- Biostatistics
Background:
- The Framingham Stroke Risk Function (FSRF) is the standard for stroke risk stratification.
- FSRF requires clinical assessments like blood pressure, glucose testing, and ECG.
- This study introduces a self-reported stroke risk function (SRSRF) for comparison.
Purpose of the Study:
- To evaluate the effectiveness of a self-reported stroke risk function (SRSRF) in stratifying stroke risk.
- To compare the predictive accuracy of SRSRF against the established Framingham Stroke Risk Function (FSRF).
Main Methods:
- Utilized data from the REGARDS study (Reasons for Geographic and Racial Differences in Stroke).
- Calculated FSRF using directly assessed risk factors and SRSRF using 13 self-reported questions.
- Employed proportional hazards analysis to assess incident stroke risk.
Main Results:
- Over 8.2 years, 939 strokes occurred in 23,983 participants.
- SRSRF and FSRF risk scores were highly correlated (r=0.852).
- SRSRF demonstrated superior stroke risk discrimination (c-statistic=0.7266) compared to FSRF (c-statistic=0.7075).
Conclusions:
- A simple self-reported questionnaire can effectively identify high-risk individuals for stroke.
- SRSRF surpasses the gold standard FSRF in predicting stroke risk.
- This tool offers clinical utility for identifying at-risk individuals and scientific value for research populations.
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