Anna Stecksén1, Eva-Lotta Glader2, Kjell Asplund2, Bo Norrving2, Marie Eriksson2. 1. From the Departments of Public Health and Clinical Medicine (A.S., E.-L.G., K.A.) and Statistics (M.E.), Umeå University, Umeå, Sweden; and Department of Clinical Sciences, Section of Neurology, Lund University, Lund, Sweden (B.N.). anna.stecksen@medicin.umu.se. 2. From the Departments of Public Health and Clinical Medicine (A.S., E.-L.G., K.A.) and Statistics (M.E.), Umeå University, Umeå, Sweden; and Department of Clinical Sciences, Section of Neurology, Lund University, Lund, Sweden (B.N.).
Abstract
BACKGROUND AND PURPOSE: Previous studies have revealed inequalities in stroke treatment based on demographics, hospital type, and region. We used the Swedish Stroke Register (Riksstroke) to test whether patient education level is associated with reperfusion (either or both of thrombolysis and thrombectomy) treatment. METHODS: We included 85 885 patients with ischemic stroke aged 18 to 80 years registered in Riksstroke between 2003 and 2009. Education level was retrieved from Statistics Sweden, and thrombolysis, thrombectomy, patient, and hospital data were obtained from Riksstroke. We used multivariable logistic regression to analyze the association between reperfusion therapy and patient education. RESULTS: A total of 3649 (4.2%) of the patients received reperfusion therapy. University-educated patients were more likely to be treated (5.5%) than patients with secondary (4.6%) or primary education (3.6%; P<0.001). The inequality associated with education was still present after adjustment for patient characteristics; university education odds ratio, 1.14; 95% confidence interval, 1.03 to 1.26 and secondary education odds ratio, 1.08; 95% confidence interval, 1.00 to 1.17 compared with primary education. Higher hospital specialization level was also associated with higher reperfusion levels (P<0.001). In stratified multivariable analyses by hospital type, significant treatment differences by education level existed only among large nonuniversity hospitals (university education odds ratio, 1.20; 95% confidence interval, 1.04-1.40; secondary education odds ratio, 1.14; 95% confidence interval, 1.01-1.29). CONCLUSIONS: We demonstrated a social stratification in reperfusion, partly explained by patient characteristics and the local hospital specialization level. Further studies should address treatment delays, stroke knowledge, and means to improve reperfusion implementation in less specialized hospitals.
BACKGROUND AND PURPOSE: Previous studies have revealed inequalities in stroke treatment based on demographics, hospital type, and region. We used the Swedish Stroke Register (Riksstroke) to test whether patient education level is associated with reperfusion (either or both of thrombolysis and thrombectomy) treatment. METHODS: We included 85 885 patients with ischemic stroke aged 18 to 80 years registered in Riksstroke between 2003 and 2009. Education level was retrieved from Statistics Sweden, and thrombolysis, thrombectomy, patient, and hospital data were obtained from Riksstroke. We used multivariable logistic regression to analyze the association between reperfusion therapy and patient education. RESULTS: A total of 3649 (4.2%) of the patients received reperfusion therapy. University-educated patients were more likely to be treated (5.5%) than patients with secondary (4.6%) or primary education (3.6%; P<0.001). The inequality associated with education was still present after adjustment for patient characteristics; university education odds ratio, 1.14; 95% confidence interval, 1.03 to 1.26 and secondary education odds ratio, 1.08; 95% confidence interval, 1.00 to 1.17 compared with primary education. Higher hospital specialization level was also associated with higher reperfusion levels (P<0.001). In stratified multivariable analyses by hospital type, significant treatment differences by education level existed only among large nonuniversity hospitals (university education odds ratio, 1.20; 95% confidence interval, 1.04-1.40; secondary education odds ratio, 1.14; 95% confidence interval, 1.01-1.29). CONCLUSIONS: We demonstrated a social stratification in reperfusion, partly explained by patient characteristics and the local hospital specialization level. Further studies should address treatment delays, stroke knowledge, and means to improve reperfusion implementation in less specialized hospitals.
Authors: Benjamin D Bray; Lizz Paley; Alex Hoffman; Martin James; Patrick Gompertz; Charles D A Wolfe; Harry Hemingway; Anthony G Rudd Journal: Lancet Public Health Date: 2018-03-15
Authors: Jusun Moon; Jinyoung Shin; Jeehye Lee; Ho Jin Jeong; Hyeongsu Kim; Jaehyeong An; Sung Hyun Jo; Kwang-Pil Ko; Jeoungbin Choi Journal: Int J Environ Res Public Health Date: 2022-03-05 Impact factor: 3.390