Tirschwell David L, Longstreth W T, Becker Kyra J, Gammans Richard E, Sabounjian LuAnn A, Hamilton Scott, Morgenstern Lewis B
Department of Neurology, Harborview Medical Center, University of Washington School of Medicine, Seattle,
Stroke. 2002 Dec;33(12):2801-6. doi: 10.1161/01.str.0000044166.28481.bc.
Prehospital stroke scales should identify stroke patients and measure stroke severity. The goal of this study was to identify a subset of the 15 items in the National Institutes of Health Stroke Scale (NIHSS-15) that measures stroke severity and predicts outcomes.
Using 2 distinct data sets from acute stroke clinical trials, we derived and validated shortened versions of the NIHSS (sNIHSS). Stepwise logistic regression and bootstrap techniques were used in selection of NIHSS-15 items. Areas under the receiver operator characteristic curve (C statistics) were used to compare predictive performance of logistic models incorporating differing versions of the NIHSS.
The derivation analyses suggested the 8 NIHSS-15 items that were most predictive of "good outcome" 3 months after stroke, in order of decreasing importance: right leg item, left leg, gaze, visual fields, language, level of consciousness, facial palsy, and dysarthria. The sNIHSS-8 comprises all 8 and the sNIHSS-5, the first 5. In the validation models, C statistics were NIHSS-15=0.80, sNIHSS-8=0.77, and sNIHSS-5=0.76. Statistical comparisons suggested that the NIHSS-15 had better predictive performance than the sNIHSS-8 or the sNIHSS-5; the absolute difference in C statistics was small. There was no significant difference between the sNIHSS-8 and the sNIHSS-5.
Much of the predictive performance of the full NIHSS-15 was retained with a shortened scale, the sNIHSS-5. Shortening the NIHSS-15 will facilitate its use during prehospital evaluations. The sNIHSS severity information may be useful to triage acute stroke patients in communities and to provide a baseline stroke severity for prehospital acute stroke trials.
院前卒中量表应能识别卒中患者并评估卒中严重程度。本研究的目的是从美国国立卫生研究院卒中量表(NIHSS - 15)的15项条目中确定一个子集,该子集可评估卒中严重程度并预测预后。
我们使用来自急性卒中临床试验的2个不同数据集,推导并验证了NIHSS的简化版本(sNIHSS)。采用逐步逻辑回归和自助法技术来选择NIHSS - 15的条目。使用受试者操作特征曲线下面积(C统计量)来比较纳入不同版本NIHSS的逻辑模型的预测性能。
推导分析表明,卒中后3个月对“良好预后”预测性最强的8项NIHSS - 15条目,按重要性递减顺序为:右腿条目、左腿、凝视、视野、语言、意识水平、面瘫和构音障碍。sNIHSS - 8包含所有这8项,sNIHSS - 5包含前5项。在验证模型中,C统计量分别为:NIHSS - 15 = 0.80,sNIHSS - 8 = 0.77,sNIHSS - 5 = 0.76。统计学比较表明,NIHSS - 15的预测性能优于sNIHSS - 8或sNIHSS - 5;C统计量的绝对差异较小。sNIHSS - 8和sNIHSS - 5之间无显著差异。
简化版量表sNIHSS - 5保留了完整的NIHSS - 15的大部分预测性能。缩短NIHSS - 15将便于其在院前评估中使用。sNIHSS的严重程度信息可能有助于社区对急性卒中患者进行分诊,并为院前急性卒中试验提供卒中严重程度基线。