Predicting Outcome in ischemic stroke: External validation of predictive risk models

• Published in: Stroke (1970) Vol. 34; no. 1; pp. 200 - 202
• Main Authors: JOHNSTON, Karen C, CONNORS, Alfred F, WAGNER, Douglas P, HALEY, E. Clarke
• Format: Journal Article
• Language: English
• Published: Hagerstown, MD Lippincott Williams & Wilkins 2003; American Heart Association, Inc
• Subjects: Aged; Biological and medical sciences; Brain Ischemia - diagnosis; Brain Ischemia - drug therapy; Calibration; Female; Humans; Male; Medical sciences; Middle Aged; Models, Statistical; Neurology; Risk; ROC Curve; Stroke - diagnosis; Stroke - drug therapy; Treatment Outcome; Vascular diseases and vascular malformations of the nervous system; Performance evaluation; Human; Nervous system diseases; Stroke; Prognosis; Cardiovascular disease; Cerebral disorder; Vascular disease; Ischemia; Statistical model; Central nervous system disease; Cerebrovascular disease; Comparative study; Brain (vertebrata)
• ISSN: 0039-2499; 1524-4628
• DOI: 10.1161/01.STR.0000047102.61863.E3

Six multivariable models predicting 3-month outcome of acute ischemic stroke have been developed and internally validated previously. The purpose of this study was to externally validate the previous models in an independent data set. We predicted outcomes for 299 patients with ischemic stroke who received placebo in the National Institute of Neurological Disorders and Stroke rt-PA trial. The model equations used 6 acute clinical variables and head CT infarct volume at 1 week as independent variables and 3-month National Institutes of Health Stroke Scale, Barthel Index, and Glasgow Outcome Scale as dependent variables. Previously developed model equations were used to forecast excellent and devastating outcome for subjects in the placebo tissue plasminogen activator data set. Area under the receiver operator characteristic curve was used to measure discrimination, and calibration charts were used to measure calibration. The validation data set patients were more severely ill (National Institutes of Health Stroke Scale and infarct volume) than the model development subjects. Area under the receiver operator characteristic curves demonstrated remarkably little degradation in the validation data set and ranged from 0.75 to 0.89. Calibration curves showed fair to good calibration. Our models have demonstrated excellent discrimination and acceptable calibration in an external data set. Development and validation of improved models using variables that are all available acutely are necessary.