Key result
Integrating ultrasound plaque characteristics with rFSRP improves stroke risk prediction, accurately reclassifying ~11% of patients.
Why the study?
Ischemic cardiovascular diseases are leading causes of death driven by atherosclerosis, and the study sought to develop a simplified approach to enhance the predictive accuracy of the revised Framingham Stroke Risk Profile by integrating ultrasound-derived plaque characteristics.
Does integrating ultrasound-derived plaque characteristics with the revised Framingham Stroke Risk Profile improve stroke risk prediction in asymptomatic patients with carotid atherosclerosis?
Cohort (n=1,782)
Yes
Does integrating ultrasound-derived plaque characteristics with the revised Framingham Stroke Risk Profile improve stroke risk prediction in asymptomatic patients with carotid atherosclerosis?
p-value: p=<0.001
Integrating ultrasound-derived plaque characteristics with the revised Framingham Stroke Risk Profile significantly improves stroke risk prediction and patient reclassification in asymptomatic carotid atherosclerosis.
May refine stroke risk stratification in asymptomatic carotid atherosclerosis; extends Framingham model but hypothesis-generating pending validation.
Background Ischemic cardiovascular diseases are leading global causes of death, largely driven by atherosclerosis. Purpose To develop a simplified approach to enhance the predictive accuracy of the revised Framingham Stroke Risk Profile (rFSRP) by integrating ultrasound-derived plaque characteristics. Material and Methods The study population consisted of 1782 asymptomatic patients with carotid plaques, prospectively enrolled from three hospitals. The patients were stratified into high-risk and low-risk groups using both the conventional rFSRP and a novel approach incorporating ultrasonic plaque features. Kaplan–Meier survival analysis and log-rank tests were utilized to evaluate stroke-free survival rates. Results Over a mean follow-up of 37 ± 15 months, 420 (23.5%) patients experienced strokes. Both univariate and multivariate analyses demonstrated a significant association between strokes and various parameters: an rFSRP score ≥10, plaque length ≥10 mm, plaque thickness ≥2 mm, and the presence of type 1 and type 2 plaque according to the Geroulakos classification. A notable disparity in stroke-free survival rate was observed between high-risk and low-risk groups when classified using the combined criteria of rFSRP and ultrasonic features ( P <0.001). The net reclassification improvement formula, accounting for reclassification accuracy, indicated that 11.2% of patients were more precisely classified under the combined criteria. In addition, patients initially deemed low-risk based solely on rFSRP, when reclassified as high-risk per the combined criteria, showed a substantial difference in stroke-free survival rate from those remaining in the low-risk category ( P <0.001). Conclusion Integrating ultrasound-derived plaque characteristics with rFSRP improves stroke risk prediction, offering a more effective clinical tool for asymptomatic carotid atherosclerosis.
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Huang et al. (2025) conducted a cohort in Asymptomatic carotid atherosclerosis (n=1,782). Combined criteria of revised Framingham Stroke Risk Profile (rFSRP) and ultrasonic plaque features vs. Conventional rFSRP alone was evaluated on Stroke-free survival (p=<0.001). Integrating ultrasound-derived plaque characteristics with the revised Framingham Stroke Risk Profile improved stroke risk prediction, accurately reclassifying 11.2% of patients (P<0.001).
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