Carotid Plaque-RADS Score Combined with Pericarotid Fat Density-An Incremental Prediction Model for Stroke Recurrence.

Rationale and objectives: This study aimed to evaluate the prognostic value of combined carotid plaque reporting and data system (RADS) score and pericarotid fat density (PFD) for predicting stroke recurrence risk, and to explore its utility in stroke risk stratification.

Methods: We developed a novel binary comprehensive risk index (CRI) that integrates the carotid plaque-RADS and PFD: low CRI (RADS <3 and PFD ≤ -74 HU) and high CRI (RADS ≥3 or PFD > -74 HU). Net reclassification improvement, Kaplan-Meier survival analysis, multivariate logistic regression, receiver operating characteristic curves (ROC), and decision curve analysis (DCA) were used to assess the predictive value of CRI over stenosis degree.

Results: During a mean follow-up period of 17.24±11.93 months, 64 of 272 patients (23.3%) experienced recurrent stroke. CRI significantly improved stroke recurrence risk stratification in mild-to-moderate stenosis patients. Kaplan-Meier survival analysis revealed significant differences in stroke recurrence rates across varying plaque-RADS and CRI (P < 0.0001). Independent predictors of stroke recurrence included plaque-RADS ≥ 3 (OR=2.68, 95% CI: 1.03-6.96), CRI (OR=8.25, 95% CI: 2.23-30.44), affected-side PFD (OR=0.97, 95% CI: 0.94-0.99), and bilateral PFD difference (OR=1.09, 95% CI: 1.05-1.13). The combined model incorporating stenosis degree, plaque-RADS, affected-side PFD, bilateral PFD difference, and CRI demonstrated superior prediction performance, achieving an area under the ROC curve of 0.892.

Conclusion: Integrating carotid plaque-RADS and PFD significantly enhances the accuracy of stroke recurrence risk prediction, especially in patients with mild-to-moderate stenosis. This combined assessment model provides valuable insights for personalized prevention and treatment strategies for stroke recurrence.