Predicting long-term independency in activities of daily living after middle cerebral artery stroke: does information from MRI have added predictive value compared with clinical information?
OBJECTIVE
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.
Center of Excellence for Rehabilitation Medicine, Rehabilitation Center De Hoogstraat Utrecht, The Netherlands. S.K.Schiemanck@amc.uva.nl
Sven K
SK
Schiemanck
Gert
G
Kwakkel
Marcel W M
MW
Post
L Jaap
LJ
Kappelle
Arie J H
AJ
Prevo
D000203:Activities of Daily Living; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D019540:Area Under Curve; D005260:Female; D006801:Humans; D020244:Infarction, Middle Cerebral Artery / Q000175:diagnosis* / Q000503:physiopathology*; D016015:Logistic Models; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D011237:Predictive Value of Tests; D011379:Prognosis; D013997:Time Factors