Factors Influencing Outcome and Treatment Effect in PROACT II

Author:

Wechsler Lawrence R.1,Roberts Robin1,Furlan Anthony J.1,Higashida Randall T.1,Dillon William1,Roberts Heidi1,Rowley Howard A.1,Pettigrew L. Creed1,Callahan Alfred S.1,Bruno Askiel1,Fayad Pierre1,Smith Wade S.1,Firszt Carolyn M.1,Schulz Gregory A.1

Affiliation:

1. From the University of Pittsburgh (L.R.W.), Pittsburgh, Pa; McMaster University (R.R.), Hamilton, Canada; the Cleveland Clinic Foundation (A.J.F.), Cleveland, Ohio; the University of California (R.T.H., W.D., W.S.S.), San Francisco; the University of Toronto (H. Roberts), Toronto, Canada; the University of Wisconsin (H.A. Rowley), Madison; the University of Kentucky (L.C.P.), Lexington; the Centennial Medical Center (A.S.C. III), Nashville, Tenn; Indiana University (A.B.), Indianapolis, Ind; the...

Abstract

Background and Purpose— The PROACT II study demonstrated a significant benefit from treatment with intra-arterial pro-urokinase (r-proUK) in patients with middle cerebral artery occlusion treated within 6 hours of stroke onset. The purpose of the current study was to examine baseline factors to determine predictors of good outcome and response to treatment. Methods— We selected from the baseline clinical, radiologic, and angiographic data variables that considered possibly related to outcome. A univariate analysis was performed to examine the association between these baseline factors and good outcome, defined as a modified Rankin scale score ≤2. A multivariate model then selected the most important variables independently influencing prognosis. A risk score for each patient was constructed on the basis of the patient’s individual values for each independent variable. Patients were stratified into risk quartiles based on their risk scores, and an odds ratio for each risk quartile was calculated. The treatment effects of each quartile were compared. Results— In the univariate analysis, screening National Institutes of Health stroke scale (NIHSS) score and age were strongly associated with good outcome. The multivariate model selected age, NIHSS score, and CT hypodensity as the most important prognostic variables. Dividing patients into quartiles based on risk scores achieved a uniform gradient of probability of good outcomes. A trend toward benefit of r-proUK treatment was seen in all risk quartiles, and no differential treatment effect was observed across risk groups. Conclusions— There was no evidence of differential effect of r-proUK across subgroups of patients stratified by risk.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Advanced and Specialised Nursing,Cardiology and Cardiovascular Medicine,Clinical Neurology

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