Abstract
Background: The information on topographic distribution of acute ischemic infarct can contribute to prediction of functional outcome. We aimed to develop a multivariate model for stroke prognostication, combining admission clinical and imaging variables, including the infarct topology. Methods: Acute ischemic stroke patients without baseline functional disability who had magnetic resonance imaging within 24 hours of onset or last-seen-well were included. The admission stroke severity was determined using the National Institutes of Health Stroke Scale (NIHSS) score. The relation between infarct location and outcome was assessed using both voxel-based and visual atlas-based analyses. The disability/death was defined by a modified Rankin Scale score greater than 2 at 3-month follow-up. Results: Among 198 patients included in this study, higher admission NIHSS score (P < .001), larger infarct volume (P < .001), and major arterial occlusions (P < .001) were associated with disability/death in univariate analyses. On voxel-based analysis, infarcts in the middle centrum semiovale, insula, and midbrain/pons were associated with higher rates of disability/death. In multivariate analysis, admission NIHSS score (P < .001), infarction of insula (P = .005), and midbrain/pons (P = .006) were independent predictors of disability/death. In receiver operating characteristics analysis, a simple 0-to-3 scoring system using these 3 variables had an area under the curve of .812 for prediction of disability/death (P < .001). Conclusions: Admission symptom severity, infarction of insula, and midbrain/pons were independent predictors of clinical outcome in acute ischemic stroke patients. The methodology of this hypothesis-generating study can help conceive quantitative population-based probabilistic models for prognostication or treatment triage in stroke patients, combining admission clinical and imaging findings-including infarct topography.
