Soliman Fatima, Gupta Ajay, Delgado Diana, Kamel Hooman, Pandya Ankur
Department of Radiology, Weill Cornell Medical College, New York, NY, USA.
Samuel J. Wood Library & C.V. Starr Biomedical Information Center, Weill Cornell Medical College, New York, NY, USA.
Neurohospitalist. 2017 Oct;7(4):169-178. doi: 10.1177/1941874417708128. Epub 2017 May 22.
Numerous stroke scales have been developed to predict functional outcomes following acute ischemic stroke. The goal of this study was to summarize functional outcome scores in stroke that incorporate neuroimaging with those that don't incorporate neuroimaging.
Searches were conducted in Ovid MEDLINE, Ovid Embase, and the Cochrane Library Database from inception to January 23, 2015. Additional records were identified by employing the "Cited by" and "View References" features in Scopus. We included studies that described stroke prognosis models or scoring systems that predict functional outcome based on clinical and/or imaging data available on presentation. Score performance was evaluated based on area under the receiver operating characteristic curve (AUC).
A total of 3300 articles were screened, yielding 14 scores that met inclusion criteria. Half (7) of the scores included neuroimaging as a predictor variable. Neuroimaging parameters included infarct size on magnetic resonance diffusion-weighted imaging, infarct size defined by computed tomography hypodensity, and hemodynamic abnormality on perfusion imaging. The modified Rankin Scale at 3 months poststroke was the most common functional outcome reported (13 of 14 scores). The AUCs ranged from 0.64 to 0.84 for scores that included neuroimaging as a predictor and 0.64 to 0.94 for scores that did not include neuroimaging. External validation has been performed for 7 scores.
Due to the marked heterogeneity in the scores and populations in which they were applied, it is unclear whether current imaging-based scores offer advantages over simpler approaches for predicting poststroke function.
已开发出众多卒中量表来预测急性缺血性卒中后的功能结局。本研究的目的是总结卒中功能结局评分,包括纳入神经影像学的评分与未纳入神经影像学的评分。
在Ovid MEDLINE、Ovid Embase和Cochrane图书馆数据库中进行检索,检索时间范围从建库至2015年1月23日。通过使用Scopus中的“被引用文献”和“查看特征识别其他记录。我们纳入了描述基于临床表现时可用的临床和/或影像数据预测功能结局的卒中预后模型或评分系统的研究。基于受试者工作特征曲线下面积(AUC)评估评分性能。
共筛选3300篇文章,产生14个符合纳入标准的评分。其中一半(7个)评分将神经影像学作为预测变量。神经影像学参数包括磁共振扩散加权成像上的梗死灶大小、计算机断层扫描低密度定义的梗死灶大小以及灌注成像上的血流动力学异常。卒中后3个月的改良Rankin量表是报告最多的功能结局(14个评分中有13个)。纳入神经影像学作为预测因素的评分的AUC范围为0.64至0.84,未纳入神经影像学的评分的AUC范围为0.64至0.94。已对7个评分进行了外部验证。
由于评分及其应用人群存在显著异质性,目前基于影像学的评分在预测卒中后功能方面是否优于更简单的方法尚不清楚。