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(Stroke. 2006;37:1050.)
© 2006 American Heart Association, Inc.
Original Contributions |
From the Center of Excellence for Rehabilitation Medicine (S.K.S., G.K., M.W.M.P., A.J.H.P.), Rehabilitation Center De Hoogstraat Utrecht, the Netherlands; Rudolf Magnus Institute of Neuroscience (S.K.S., G.K., M.W.M.P., L.J.K., A.J.H.P.), University Medical Center Utrecht, the Netherlands; Institute for Rehabilitation Research (M.W.M.P.), Hoensbroek, the Netherlands; and Department of Neurology (L.J.K.), University Medical Center Utrecht, the Netherlands.
Correspondence to Sven Schiemanck, Academic Medical Center (AMC), Department of Rehabilitation, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands. E-mail S.K.Schiemanck{at}amc.uva.nl
Background and Purpose 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.
Methods 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.
Results 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.
Conclusions 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.
Key Words: activities of daily living magnetic resonance imaging stroke
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