22. European Stroke Conference Stroke prevention (PO 740 - 784 ) 740 Stroke prevention Patient and bystander educational levels influence on delay between stroke onset and hospital arrival J. Pereira de Sá1, M. Castelo-Branco2, L. Patrao3, R. Tjeng4 Faculty of Health Sciences University of Beira Interior, Covilhã, PORTUGAL1, Hospital Center of Cova da Beira, Covilhã, PORTUGAL2, Faculty of Health Sciences University of Beira Interior, Covilhã, PORTUGAL3, Faculty of Health Sciences University of Beira Interior, Covilhã, PORTU-GAL4 Background After a stroke, the phrase “time is brain” means that in stroke care there are interventions that could impact on prognosis that are time dependent. Extended research about factors that influence emer-gency arrival time after acute stroke, “stroke-to-door time” has been developed during recent years. Presence of bystander has been associated with early arrival and greater stroke awareness. However, little research has been conducted to know if bystander age and educational level is associated with early arrival to emergency department. The study main goal is to access if population social and ed-ucational characteristics influence time to hospital arrival after stroke onset. Methods A population of 274 patients has been admitted to the hospital Stroke Unit during 2011. 168 of these patients matched inclusion criteria: discharge diagnosis of acute stroke, not institutionalized, living in Portugal and having telephone number. These patients were initially contacted by letter with in-formation about the research and afterwards answered a survey by phone call. IBM SPSS Statistics 21® was used for data analysis. Results A hundred and one patients answered the phone call and accepted to participate. Mean age was 72 years old, 61% were man and 55% lived in rural areas. 26% were illiterates, 63% completed primary education and less than 11% completed secondary or tertiary education. Sixty seven per cent were accompanied at the moment of symptoms onset, bystanders mean age was 63 years old, 13% were illiterates, 62% completed primary education, 18% completed secondary education and 7% complet-ed tertiary education. 46,5% used ambulance and 68,3% arrived to the hospital before 4,5h after the stroke onset. Chi-square test showed no correlation between the variables. Conclusion No relation was found between patient’s educational level, social environment, presence of a by-stander, bystander’s age or educational level with shorter stroke-to-door time. 736 © 2013 S. Karger AG, Basel Scientific Programme 741 Stroke prevention Studies in Platelet Aggregation - Comparative evaluation of Visual Count Method and that by Automatic Platelet Aggregometer P. M. Dalal1, R Buran2, P Bhat3 LKMM Trust Research Centre, At Lilavati Hospital, A-791, Bandra Reclamation, Mumbai, INDIA1, LKMM Trust Research Centre, At Lilavati Hospital, A-791, Bandra Reclamation, Mumbai, INDIA2, LKMM Trust Research Centre, At Lilavati Hospital, A-791, Bandra Reclamation, Mumbai, INDIA3 Introduction: Use of antiplatelet agents (aspirin) is one of the important strategies to prevent rising stroke incidence in developing countries. We decided to study the dose relationship of Aspirin and the degree of inhibition of platelet aggregation by Aggregometer (Chrono – Log Corporation model 700) and also to compare the results by Visual Count Method (platelet counting chamber-Neubau-er’s chamber). Background: To prevent recurrent ischemic stroke , platelet anti aggregants like aspirin in dose of 75mg - 150mg per day has been advocated, which brings down the rate of recurrence to the tune of 28% - 30%. However, there is no standardized dose for aspirin use. Methods: Samples were drawn from stroke patients who were willing to undergo above test on vol-untary basis, volunteers were drawn from out patient department. Platelet aggregation was tested simultaneously by Automatic Platelet Aggregometer and Visual count of platelet on Neubauer cham-ber. Comparison of platelet aggregation by both methods was done using reagents such as Adenos-ine diphosphate (ADP), Collagen and Arachidonic acid (AA). Results: Platelet aggregation was tested on 38 (ICVD) cases, 3 (ICH) cases, and 22 (Non Stroke Healthy Controls) and matched with 64 Healthy Controls on no medication. The mean aggregation values using ADP, collagen and AA by machine method in cases was 45% and by visual count meth-od was 37% (p=0.9485). The mean aggregation values by machine method in controls was 66.3% and by visual count method was 65.3% (p=1.00). The paired results of the samples were analyzed for agreement. When ADP was used, the agreement between the two methods was closer - 0.5% (95% CI, -2.5% to 1.5%) than when collagen -2.5% (95% CI, -0.2% to 5%) was used. Conclusion: The Visual Count Method using ADP seems clinically acceptable for estimating platelet aggregation and monitoring anti-platelet therapy, in developing country like India, where prohibitive cost of Aggregometer is a drawback. One can establish simple laboratory techniques using Visual Count Method as main stay.
Karger_ESC London_2013
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