Helicobacter pylori infection contributes to high risk of ischemic stroke: evidence from a meta-analysis

Chronic infection of Helicobacter pylori (H. pylori) in ischemic stroke (IS) incidence has been previously studied in several publications; however, conflicting results have been reported. A meta-analysis was used to assess whether chronic infection of H. pylori was associated with risk of IS, and which of the following was more effective for predication of IS risk, antibody IgG of H. pylori (anti-H. pylori IgG), antibody IgG of cytotoxin-associated gene-A (anti-Cag A IgG) or the ¹³C-urea breath test. We searched the databases of Medline and Embase, and latest update was January 1, 2012. Case–control studies were considered to be eligible. The odds ratio (OR) and 95 % confidence interval (95 % CI) were calculated using the random-effect model. A total of 13 studies including 4,041 participants were included in this meta-analysis. Of these studies, ten, four and four studies were for anti-H. pylori IgG, anti-Cag A IgG and the ¹³C-urea breath test, respectively. Combined analysis indicated that positive anti-H. pylori IgG, anti-Cag A IgG and ¹³C-urea breath test were significantly associated with increased risk of IS, respectively, and positive anti-Cag A IgG was more effective for predication of IS risk [OR (95 % CI) = 1.60 (1.21–2.11), P _{heterogeneity} = 0.001 for positive versus negative anti-H. pylori IgG; 2.33 (1.76–3.09), P _{heterogeneity} = 0.71 for positive versus negative anti-Cag A IgG and 1.65 (1.11–2.47), P _{heterogeneity} = 0.17 for positive versus negative ¹³C-urea breath test]. In addition, we found that positive anti-H. pylori IgG was closely associated with risk of IS caused by atherosclerosis and small artery disease, but not for cardioembolic IS. This meta-analysis indicated that chronic H. pylori infection was significantly associated with an increased risk of IS, especially for non-cardioembolic IS. Compared with anti-H. pylori IgG and the ¹³C-urea breath test, anti-Cag A IgG seemed more effective for prediction of risk of IS.