(Stroke. 2000;31:448.)
© 2000 American Heart Association, Inc.
Original Contributions |
Presented in part at the First Neurology Outcomes Research Conference of the American Neurological Association, Montreal, Canada, October 17, 1998.
From the Departments of Neurology (K.C.J., E.C.H.) and Health Evaluation Sciences (K.C.J., A.F.C., D.P.W., W.A.K., X.-Q.W.), University of Virginia, Charlottesville.
Correspondence to Karen C. Johnston, MD, University of Virginia Health System, Department of Neurology, No. 394, Charlottesville, VA 22908. E-mail kj4v{at}virginia.edu
Background and PurposeThe great variability of outcome seen in stroke patients has led to an interest in identifying predictors of outcome. The combination of clinical and imaging variables as predictors of stroke outcome in a multivariable risk adjustment model may be more powerful than either alone. The purpose of this study was to determine the multivariable relationship between infarct volume, 6 clinical variables, and 3-month outcomes in ischemic stroke patients.
MethodsIncluded in the study were 256 eligible patients from the Randomized Trial of Tirilazad Mesylate in Acute Stroke (RANTTAS). Six clinical variables and 1-week infarct volume were the prespecified predictor variables. The National Institutes of Health Stroke Scale, Barthel Index, and Glasgow Outcome Scale were the outcomes. Multivariable logistic regression techniques were used to develop the model equations, and bootstrap techniques were used for internal validation. Predictive performance of the models was assessed for discrimination with receiver operator characteristic (ROC) curves and for calibration with calibration curves.
ResultsThe predictive models had areas under the ROC curve of 0.79 to 0.88 and demonstrated nearly ideal calibration curves. The areas under the ROC curves were statistically greater (P<0.001) with both clinical and imaging information combined than with either alone for predicting excellent recovery and death or severe disability.
ConclusionsCombined clinical and imaging variables are predictive of 3-month outcome in ischemic stroke patients. Demonstration of this relationship with acute clinical variables and 1-week infarct information supports future attempts to predict 3-month outcome with all acute variables.
Key Words: models, statistical prognosis stroke, ischemic stroke outcome
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