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Abstract
The impact of small vessel disease (SVD) on stroke outcome was investigated either separately for its single features in isolation or for SVD sum score measuring a qualitative (binary) assessment of SVD-lesions. We aimed to investigate which SVD feature independently impacts the most on stroke outcome and to compare the continuous versus binary SVD assessment that reflects pronouncement and presence correspondingly. Patients with a first-ever anterior circulation ischemic stroke were retrospectively investigated. We performed an ordered logistic regression analysis to predict stroke outcome (mRS 3 months, 0–6) using age, stroke severity, and pre-stroke disability as baseline input variables and adding SVD-features (lacunes, microbleeds, enlarged perivascular spaces, white matter hyperintensities) assessed either continuously (model 1) or binary (model 2). The data of 873 patients (age 67.9 ± 15.4, NIHSS 24 h 4.1 ± 4.8) was analyzed. In model 1 with continuous SVD-features, the number of microbleeds was the only independent predictor of stroke outcome in addition to clinical parameters (OR 1.21; 95% CI 1.07–1.37). In model 2 with the binary SVD assessment, only the presence of lacunes independently improved the prediction of stroke outcome (OR 1.48, 1.1–1.99). In a post hoc analysis, both the continuous number of microbleeds and the presence of lacunes were independent significant predictors. Thus, the number of microbleeds evaluated continuously and the presence of lacunes are associated with stroke outcome independent from age, stroke severity, pre-stroke disability and other SVD-features. Whereas the presence of lacunes is adequately represented in SVD sum score, the microbleeds assessment might require another cutoff and/or gradual scoring, when prediction of stroke outcome is needed.
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Details
1 University of Bern, University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, University Hospital Bern, Bern, Switzerland (GRID:grid.5734.5) (ISNI:0000 0001 0726 5157)
2 University of Bern, Department of Neurology, Inselspital, University Hospital Bern, Bern, Switzerland (GRID:grid.5734.5) (ISNI:0000 0001 0726 5157)
3 University of Bern, Department of Neurology, Inselspital, University Hospital Bern, Bern, Switzerland (GRID:grid.5734.5) (ISNI:0000 0001 0726 5157); University of Basel, Department of Neurology, University Hospital Basel, Basel, Switzerland (GRID:grid.6612.3) (ISNI:0000 0004 1937 0642)