BACKGROUND AND PURPOSE: Today, treatment of acute stroke consists of tissue-type plasminogen activator (tPA), admission to a stroke unit, and aspirin. Although tPA treatment is the most effective, there is substantial undertreatment. Centralized care may affect rate, timing, and outcome of thrombolysis compared to decentralized treatment in community hospitals. The present study aimed to assess the impact of organizational models on the proportion of patients undergoing tPA treatment. METHODS: A prospective, multicenter, observational study among 13 hospitals in the North of the Netherlands was conducted. In the centralized model, tPA treatment for 4 hospitals was administered in 1 stroke center. The decentralized model comprised 9 community hospitals. Primary outcome was the proportion of patients treated with tPA. Secondary outcome measures were proportion of patients arriving within 4.5 hours, safety, 90-day functional outcome, and onset-to-door, door-to-needle, and onset-to-needle times. Potential confounders were adjusted using logistic regression analysis. RESULTS: Two hundred eighty-three and 801 ischemic stroke patients were enrolled in the centralized and decentralized settings. Numbers of patients treated with tPA were 62 (21.9%) and 113 (14.1%) (OR, 1.72; 95% CI, 1.22-2.43). Adjusting for potential confounders did not alter results (OR, 2.03; 95% CI, 1.39-2.96). In the centralized setting, significantly more patients arrived at the hospital within the 4.5-hour time window (P<0.01), and shorter door-to-needle times were reached (35 versus 47 minutes). Other secondary outcome measures did not differ across setting. CONCLUSIONS: In a centralized setting, the results demonstrate a 50% increased likelihood of treatment. Prehospital factors seem to contribute to this result.
BACKGROUND AND PURPOSE: Today, treatment of acute stroke consists of tissue-type plasminogen activator (tPA), admission to a stroke unit, and aspirin. Although tPA treatment is the most effective, there is substantial undertreatment. Centralized care may affect rate, timing, and outcome of thrombolysis compared to decentralized treatment in community hospitals. The present study aimed to assess the impact of organizational models on the proportion of patients undergoing tPA treatment. METHODS: A prospective, multicenter, observational study among 13 hospitals in the North of the Netherlands was conducted. In the centralized model, tPA treatment for 4 hospitals was administered in 1 stroke center. The decentralized model comprised 9 community hospitals. Primary outcome was the proportion of patients treated with tPA. Secondary outcome measures were proportion of patients arriving within 4.5 hours, safety, 90-day functional outcome, and onset-to-door, door-to-needle, and onset-to-needle times. Potential confounders were adjusted using logistic regression analysis. RESULTS: Two hundred eighty-three and 801 ischemic strokepatients were enrolled in the centralized and decentralized settings. Numbers of patients treated with tPA were 62 (21.9%) and 113 (14.1%) (OR, 1.72; 95% CI, 1.22-2.43). Adjusting for potential confounders did not alter results (OR, 2.03; 95% CI, 1.39-2.96). In the centralized setting, significantly more patients arrived at the hospital within the 4.5-hour time window (P<0.01), and shorter door-to-needle times were reached (35 versus 47 minutes). Other secondary outcome measures did not differ across setting. CONCLUSIONS: In a centralized setting, the results demonstrate a 50% increased likelihood of treatment. Prehospital factors seem to contribute to this result.
Authors: Lesli E Skolarus; William J Meurer; Krithika Shanmugasundaram; Eric E Adelman; Phillip A Scott; James F Burke Journal: Stroke Date: 2015-06-02 Impact factor: 7.914
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Authors: A Haass; S Walter; A Ragoschke-Schumm; I Q Grunwald; M Lesmeister; A V Khaw; K Fassbender Journal: Nervenarzt Date: 2014-02 Impact factor: 1.214
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Authors: Tom van Seeters; Geert Jan Biessels; Irene C van der Schaaf; Jan Willem Dankbaar; Alexander D Horsch; Merel J A Luitse; Joris M Niesten; Willem P T M Mali; L Jaap Kappelle; Yolanda van der Graaf; Birgitta K Velthuis Journal: BMC Neurol Date: 2014-02-25 Impact factor: 2.474
Authors: Maarten M H Lahr; Durk-Jouke van der Zee; Patrick C A J Vroomen; Gert-Jan Luijckx; Erik Buskens Journal: PLoS One Date: 2013-11-18 Impact factor: 3.240
Authors: Carla H C Moro; Anderson R R Gonçalves; Alexandre L Longo; Patricia G Fonseca; Rodrigo Harger; Débora B Gomes; Mariana C Ramos; Aline L G Estevam; Cristiane S Fissmer; Adriana C Garcia; Vivian Nagel; Norberto L Cabral Journal: Cerebrovasc Dis Extra Date: 2013-12-20