Govan Lindsay, Langhorne Peter, Weir Christopher J
Stroke. 2009 Oct;40(10):3396-9. doi: 10.1161/STROKEAHA.109.557645. Epub 2009 Aug 6.
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.
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.
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.
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.
卒中严重程度和依赖程度常被分类，以便进行随机分组或分析的分层。然而，不同卒中量表所使用的分类是否等效尚不确定。我们研究了对严重程度和依赖程度进行分类所保留的信息量，以及当前使用的截断值在不同卒中量表之间是否等效。
卒中严重程度和依赖程度已被分为轻度、中度或重度。我们研究了2个急性卒中单元队列，测量了斯堪的纳维亚卒中量表（SSS）、改良Rankin量表（mRS）、Barthel指数（BI）和改良国立卫生研究院卒中量表（mNIHSS）。检查受试者工作特征（ROC）曲线，以确定完整量表和分类量表预测死亡和依赖程度的能力。加权kappa分析评估分类量表之间的一致性。
当对量表进行分类时，ROC曲线下面积显著减小；然而，差异很小，可能在实际中并不重要。分类时，BI、mRS和SSS相互之间一致性极佳，而mNIHSS与mRS和BI一致性较好。
对卒中量表进行分类时，几乎没有丢失预测信息。分类量表之间有较好到几乎完美的一致性。因此，在分析中使用和分类各种卒中严重程度或依赖程度量表是可以接受的。
