Schiemanck Sven K, Kwakkel Gert, Post Marcel W M, Kappelle L Jaap, Prevo Arie J H
Center of Excellence for Rehabilitation Medicine, Rehabilitation Center De Hoogstraat Utrecht, The Netherlands.
Stroke. 2006 Apr;37(4):1050-4. doi: 10.1161/01.STR.0000206462.09410.6f. Epub 2006 Feb 23.
To investigate whether neuroimaging information has added predictive value compared with clinical information for independency in activities of daily living (ADL) 1 year after stroke.
Seventy-five first-ever middle cerebral artery stroke survivors were evaluated in logistic regression analyses. Model 1 was derived on the basis of clinical variables; for model 2, neuroimaging variables were added to model 1. Independent variables were stroke severity (National Institutes of Health Stroke Scale), consciousness (Glasgow Coma Scale), urinary continence, demographic variables (age, gender, relationship, educational level), hospital of admission, and clinical instruments: sitting balance (trunk control test), motor functioning (Motricity Index), and ADL (Barthel Index). Neuroimaging variables, determined on conventional MRI scans, included: number of days to scanning, lesion volume, lesion localization (cortex/subcortex), hemisphere, and the presence of white matter lesions. ADL independency was defined as 19 and 20 points on Barthel Index. Differences in accuracy of prediction of ADL independence between models 1 and 2 were analyzed by comparing areas under the curve (AUC) in a receiver operating characteristic analysis.
Model 1 contained as significant predictors: age and ADL (AUC 0.84), correctly predicting 77%. In model 2, number of days to scanning, hemisphere, and lesion volume were added to model 1, increasing the AUC from 0.84 to 0.87, accurately predicting 83% of the surviving patients.
Clinical variables in the second week after stroke are good predictors for independency in ADL 1 year after stroke. Neuroimaging variables on conventional MRI scans do not have added value in long-term prediction of ADL.
探讨与临床信息相比,神经影像学信息对卒中后1年日常生活活动(ADL)独立性是否具有额外的预测价值。
对75例首次发生大脑中动脉卒中的幸存者进行逻辑回归分析。模型1基于临床变量得出;模型2在模型1的基础上加入神经影像学变量。自变量包括卒中严重程度(美国国立卫生研究院卒中量表)、意识(格拉斯哥昏迷量表)、尿失禁、人口统计学变量(年龄、性别、关系、教育水平)、入院医院以及临床指标:坐位平衡(躯干控制测试)、运动功能(运动指数)和ADL(巴氏指数)。通过常规MRI扫描确定的神经影像学变量包括:扫描天数、病灶体积、病灶定位(皮质/皮质下)、半球以及白质病变的存在情况。ADL独立性定义为巴氏指数达到19分和20分。通过比较受试者工作特征分析中的曲线下面积(AUC),分析模型1和模型2对ADL独立性预测准确性的差异。
模型1包含的显著预测因素为:年龄和ADL(AUC为0.84),正确预测率为77%。在模型2中,扫描天数、半球和病灶体积被加入到模型1中,AUC从0.84增加到0.87,准确预测了83%的存活患者。
卒中后第二周的临床变量是卒中后1年ADL独立性的良好预测因素。常规MRI扫描的神经影像学变量在ADL的长期预测中没有额外价值。