Published online before print October 26, 2006, doi: 10.1161/01.STR.0000249054.96644.c6
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(Stroke. 2006;37:2957.)
© 2006 American Heart Association, Inc.
Original Contributions |
The Stroke–Thrombolytic Predictive Instrument
A Predictive Instrument for Intravenous Thrombolysis in Acute Ischemic Stroke
From Institute for Clinical Research and Health Policy Studies and Department of Medicine (D.M.K., H.P.S., R.R.), Tufts-New England Medical Center, Tufts University School of Medicine, Boston, Mass; Boehringer Ingelheim (E.B.), Ingelheim, Germany; Department of Neurology (W.H.), University of Heidelberg, Heidelberg, Germany.
Correspondence to David M. Kent, MD, MS, Institute for Clinical Research and Health Policy Studies, Tufts-New England Medical Center, 750 Washington St, #63, Boston, MA, 02111. E-mail Dkent1{at}tufts-nemc.org
Background and Purpose— Many patients with ischemic stroke eligible for recombinant tissue plasminogen activator (rt-PA) are not treated in part because of the risks and benefits perceived by treating physicians. Therefore, we aimed to develop a Stroke-Thrombolytic Predictive Instrument (TPI) to aid physicians considering thrombolysis for stroke.
Methods— Using data from 5 major randomized clinical trials (n=2184) testing rt-PA in the 0- to 6-hour window, we developed logistic regression equations using clinical variables as potential predictors of a good outcome (modified Rankin Scale score 
1) and of a catastrophic outcome (modified Rankin Scale score 
5), with and without rt-PA. The models were internally validated using bootstrap re-sampling.
Results— To predict good outcome, in addition to rt-PA treatment, 7 variables significantly affected prognosis and/or the treatment-effect of rt-PA: age, diabetes, stroke severity, sex, previous stroke, systolic blood pressure, and time from symptom onset. To predict catastrophic outcome, only age, stroke severity, and serum glucose were significant; rt-PA treatment was not. For patients treated within 3 hours, the median predicted probability of a good outcome with rt-PA was 42.9% (interquartile range [IQR]=18.6% to 64.7%) versus 25.3% (IQR=9.8% to 46.2%) without rt-PA; the median predicted absolute benefit was 12.5% (IQR=5.1% to 21.0%). The median probability for a catastrophic outcome, with or without, rt-PA was 15.2% (IQR=8.0% to 31.2%). The area under the receiver-operator characteristic curve was 0.788 for the model predicting good outcome and 0.775 for the model predicting bad outcome.
Conclusions— The Stroke-TPI predicts good and bad functional outcomes with and without thrombolysis. Incorporated into a usable tool, it may assist in decision-making.
Key Words: acute care • acute Rx • acute stroke • clinical decision support • emergency medicine • predictive models • thrombolysis • thrombolytic Rx
Related Article:
Stroke 2006 37: 2865-2866.
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