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Background and Purpose: Timely intravenous (IV) thrombolysis for acute ischemic stroke is associated with better clinical outcomes. Acute stroke care implemented with “Stroke Code” (SC) may increase IV tissue plasminogen activator (tPA) administration. The present study aimed to investigate the impact of SC on thrombolysis. Methods: The study period was divided into the “pre-SC era” (January 2006 to July 2010) and “SC era” (August 2010 to July 2013). Demographics, critical times (stroke symptom onset, presentation to the emergency department, neuroimaging, thrombolysis), stroke severity, and clinical outcomes were recorded and compared between the two eras. Results: During the study period, 5957 patients with acute ischemic stroke were admitted; of these, 1301 (21.8%) arrived at the emergency department within 3 h of stroke onset and 307 (5.2%) received IV-tPA. The number and frequency of IV-tPA treatments for patients with an onset-to-door time of <3 h increased from the pre-SC era (n = 91, 13.9%) to the SC era (n = 216, 33.3%) (P<0.001). SC also improved the efficiency of IV-tPA administration; the median door-to-needle time decreased (88 to 51 min, P<0.001) and the percentage of door-to-needle times ≤60 min increased (14.3% to 71.3%, P<0.001). The SC era group tended to have more patients with good outcome (modified Rankin Scale ≤2) at discharge (49.5 vs. 39.6%, P = 0.11), with no difference in symptomatic hemorrhage events or in-hospital mortality. Conclusion: The SC protocol increases the percentage of acute ischemic stroke patients receiving IV-tPA and decreases door-to-needle time. [ABSTRACT FROM AUTHOR]

In the proposed approach, financial data are collected automatically and are input to a GM(1,1) prediction model to forecast the future trends of the collected data. The forecast data are then reduced using a GM(1,N) model, classified using a K-Means clustering algorithm, and processed by a Rough Set (RS) classification module which selects appropriate investment stocks. Finally, a Minimum Variance At Risk (MVAR) scheme comprising five Grey Relational Analysis (GRA) models and the Markowitz means-variance (MV) model is employed to identify the efficient frontier which achieves the optimal trade off between the minimum risk and the maximum rate of return. [ABSTRACT FROM AUTHOR]