Abstract WP166: Prediction of Recurrent Stroke in Lacunar Stroke Patients

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Abstract

Introduction: The previously published cerebral SVD Score is a four-point rating scale based on the four cardinal MRI markers of SVD: moderate-severe white matter hyperintensities, , lacune(s), moderate-severe enlarged perivascular spaces (PVS), and microbleed(s). We evaluated the score’s ability to predict recurrent stroke in the Secondary Prevention of Small Subcortical Strokes (SPS3) Trial.

Methods: One point each was awarded for these 4 MRI findings: max periventricular Fazekas score = 3 and/or max subcortical Fazekas score > 2; >1 cerebral microbleed 2 (i.e. > 11 PVS unilaterally); > 1 old lacune (3-15 mm) on FLAIR/T1. Annualized rates of recurrent stroke were computed assuming a Poisson model, and c-statistics were calculated for the SVD score model and for two other previously published SPS3 derived models.

Results: Of 3020 participants, 1137 had complete data available for SVD scoring. Prevalence of SVD scores 0, 1, 2, 3, and 4 were 19% (n=219), 29% (n=325), 24% (n=277), 18% (n=200), and 10% (n=116). PVS (55%) were most common, followed by moderate-severe white matter hyperintensities (45), lacunes (41), and microbleeds (30). Recurrent stroke rates did not strictly increase with increasing SVD score, i.e. rates were 2.4%/pt-yr (95% CI 1.5, 3.9), 1.4 (0.8, 2.3), 2.0 (1.3, 3.2), 3.8 (2.5, 5.7), and 3.2 (1.8, 5.6) respectively. When SVD scores of 0-2 vs. 3-4 were grouped and compared with two other models for predicting recurrent stroke in this cohort, the SVD score model did not outperform. (Table)

Conclusions: SVD score features were very common in the SPS3 cohort. Higher (3-4) vs. lower (0-2) SVD scores predicted recurrent stroke with similar predictive ability to models including clinical risk factors only +/- fewer MRI features. Further testing of the SVD score is warranted.

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