The application of extracorporeal membrane oxygenation in adults has been increasing, but infections occurring during extracorporeal membrane oxygenation use are rarely described.Methods: We retrospectively analyzed the prospectively collected data on nosocomial infection surveillance of 334 patients aged 16 years or more undergoing their first extracorporeal membrane oxygenation for more than 48 hours at a university hospital from 1996 to 2007 for respiratory (20.4%) and cardiac (79.6%) support.Results: During a total of 2559 extracorporeal membrane oxygenation days, 55 episodes of infections occurred in 45 patients (13.5%), including 38 bloodstream (14.85 per 1000 extracorporeal membrane oxygenation days), 6 surgical site, 4 respiratory tract, 3 urinary tract, and 4 other infections. Stenotrophomonas maltophilia (16.7%) and Candida species (14.6%) were the predominant blood isolates. In stepwise logistic regression analysis, longer duration of extracorporeal membrane oxygenation use (odds ratio 1.003; 95% confidence interval, 1.001-1.005; P ¼ .004), mechanical complications (odds ratio, 4.849; 95% confidence interval, 1.569-14.991; P ¼ .006), autoimmune disease (odds ratio, 6.997; 95% confidence interval, 1.541-31.766; P ¼ .012), and venovenous mode (odds ratio, 4.473; 95% confidence interval, 1.001-19.977; P ¼ .050) were independently associated with a higher risk for infections during extracorporeal membrane oxygenation use. Overall in-hospital mortality was 68.3%, and its independent risk factors included older age (odds ratio, 1.037; 95% confidence interval, 1.021-1.054; P < .001), neurologic complications (odds ratio, 51.153; 95% confidence interval, 6.773-386.329; P < .001), and vascular complications (odds ratio, 1.922; 95% confidence interval, 1.112-3.320; P < .001), but not infections during extracorporeal membrane oxygenation use.Conclusions: Bloodstream infection was the most common infection during extracorporeal membrane oxygenation use. Duration of extracorporeal membrane oxygenation, mechanical complications, autoimmune disease, and venovenous mode seemed to be independently associated with infections.

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Exome sequencing (exome-seq) has aided in the discovery of a huge amount of mutations in cancers, yet challenges remain in converting oncogenomics data into information that is interpretable and accessible for clinical care. We constructed DriverDB (http://ngs.ym.edu.tw/driverdb/), a database which incorporates 6079 cases of exome-seq data, annotation databases (such as dbSNP, 1000 Genome and Cosmic) and published bioinformatics algorithms dedicated to driver gene/mutation identification. We provide two points of view, ‘Cancer’ and ‘Gene’, to help researchers to visualize the relationships between cancers and driver genes/mutations. The ‘Cancer’ section summarizes the calculated results of driver genes by eight computational methods for a specific cancer type/dataset and provides three levels of biological interpretation for realization of the relationships between driver genes. The ‘Gene’ section is designed to visualize the mutation information of a driver gene in five different aspects. Moreover, a ‘Meta-Analysis’ function is provided so researchers may identify driver genes in customer-defined samples. The novel driver genes/mutations identified hold potential for both basic research and biotech applications.