Categorizing Stroke Prognosis Using Different Stroke Scales

BACKGROUND AND PURPOSE: Stroke severity and dependency are often categorized to allow stratification for randomization or analysis. However, there is uncertainty whether the categorizations used for different stroke scales are equivalent. We investigated the amount of information retained by categorizing severity and dependency, and whether the currently used cut-offs are equivalent across different stroke scales. METHODS: Stroke severity and dependency have been categorized as mild, moderate, or severe. We studied 2 acute stroke unit cohorts, measuring Scandinavian Stroke Scale (SSS), modified Rankin Scale (mRS), Barthel Index (BI), and modified National Institutes of Health Stroke Scale (mNIHSS). Receiver operating characteristic (ROC) curves were examined to determine the ability of full and categorized scales to predict death and dependency. A weighted kappa analysis assessed agreement between the categorized scales. RESULTS: When scales are categorized, the area under the ROC curve is significantly reduced; however, the differences are small and may not be practically important. BI, mRS, and SSS all have excellent agreement with each other when categorized, whereas mNIHSS has substantial agreement with mRS and BI. CONCLUSIONS: Little predictive information is lost when stroke scales are categorized. There is substantial to almost perfect agreement among categorized scales. Therefore the use and categorization of a variety of stroke severity or dependency scales is acceptable in analyses.