Acute Stroke Unit, Neurology Service and Institute of Social and Preventive Medicine, Centre HospitalierUniversitaire Vaudois and University of Lausanne, Lausanne, Switzerland.
Neurology. 2012 Jun 12;78(24):1916-22. doi: 10.1212/WNL.0b013e318259e221. Epub 2012 May 30.
To develop and validate a simple, integer-based score to predict functional outcome in acute ischemic stroke (AIS) using variables readily available after emergency room admission.
Logistic regression was performed in the derivation cohort of previously independent patients with AIS (Acute Stroke Registry and Analysis of Lausanne [ASTRAL]) to identify predictors of unfavorable outcome (3-month modified Rankin Scale score >2). An integer-based point-scoring system for each covariate of the fitted multivariate model was generated by their β-coefficients; the overall score was calculated as the sum of the weighted scores. The model was validated internally using a 2-fold cross-validation technique and externally in 2 independent cohorts (Athens and Vienna Stroke Registries).
Age (A), severity of stroke (S) measured by admission NIH Stroke Scale score, stroke onset to admission time (T), range of visual fields (R), acute glucose (A), and level of consciousness (L) were identified as independent predictors of unfavorable outcome in 1,645 patients in ASTRAL. Their β-coefficients were multiplied by 4 and rounded to the closest integer to generate the score. The area under the receiver operating characteristic curve (AUC) of the score in the ASTRAL cohort was 0.850. The score was well calibrated in the derivation (p = 0.43) and validation cohorts (0.22 [Athens, n = 1,659] and 0.49 [Vienna, n = 653]). AUCs were 0.937 (Athens), 0.771 (Vienna), and 0.902 (when pooled). An ASTRAL score of 31 indicates a 50% likelihood of unfavorable outcome.
The ASTRAL score is a simple integer-based score to predict functional outcome using 6 readily available items at hospital admission. It performed well in double external validation and may be a useful tool for clinical practice and stroke research.
利用急诊后可获得的变量，开发并验证一种简单的基于整数的评分系统，以预测急性缺血性脑卒中（AIS）的功能结局。
对先前独立的 AIS 患者（急性脑卒中登记和分析洛桑研究[ASTRAL]）的推导队列进行逻辑回归，以确定不良结局（3 个月改良 Rankin 量表评分>2）的预测因子。通过拟合多变量模型的每个协变量的β系数，为每个协变量生成基于整数的评分系统；总体评分计算为加权评分的总和。该模型通过 2 折交叉验证技术进行内部验证，并在 2 个独立队列（雅典和维也纳脑卒中登记研究）中进行外部验证。
年龄（A）、入院 NIH 脑卒中量表评分测量的脑卒中严重程度（S）、发病至入院时间（T）、视野范围（R）、急性血糖（A）和意识水平（L）被确定为 ASTRAL 队列中 1645 例患者不良结局的独立预测因子。他们的β系数乘以 4 并四舍五入到最接近的整数以生成评分。评分在 ASTRAL 队列中的受试者工作特征曲线（ROC）下面积（AUC）为 0.850。评分在推导（p=0.43）和验证队列（0.22[雅典，n=1659]和 0.49[维也纳，n=653]）中均得到很好的校准。AUC 分别为 0.937（雅典）、0.771（维也纳）和 0.902（汇总）。ASTRAL 评分为 31 分提示不良结局的可能性为 50%。
ASTRAL 评分是一种简单的基于整数的评分系统，可使用入院时 6 个易于获得的项目预测功能结局。它在双外部验证中表现良好，可能是临床实践和脑卒中研究的有用工具。
