This project currently includes four studies each of which is a component of the Stroke Data Bank or its precursor, the Pilot Stroke Data Bank. The studies are: (1) Evolving Stroke. Using demographic, history, clinical and laboratory data, this study describes the temporal course of stroke-in-evolution and attempts to identify factors that cause or contribute to evolution. (2) Stroke Diagnosis. A set of diagnostic algorithms for stroke classification based on laboratory and clinical findings were developed during the pilot project. The usefulness of the algorithms is being evaluated for differentiating etiology and predicting outcome. Plans for analyses have been formulated. (3) Utility of diagnostic tests. A variety of diagnostic tests (including angiography, CT scanning and noninvasive cardiac and vascular tests) are available for the study of the stroke patient. We intend to investigate the utility of each of these tests in establishing stroke cause and examine the utility of these tests in predicting survival rate, degree of recovery, and risk of stroke recurrence. Study designs and analyses plans have been formulated for this study. (4) Prognostic factors for 30 day mortality. This study determines a set of prognostic factors available shortly after hospitalization for ischemic strokes that are predictive of 30 day mortality. A logistic regression model has been developed based on 620 stroke cases with 52 deaths within 30 days post onset available from the pilot project. Factors (112 in all) were initially screened by univariate statistical methods and those screened positive were used multivariately in a logistic model. Cross validation of the model will be accomplished on the current Stroke Data Bank.
