Estimation of Health and Economic Benefits of a Small Automatic External Defibrillator for Rapid Treatment of Sudden Cardiac Arrest (SMART): A Cost-Effectiveness Analysis.

Background: Sudden cardiac arrest (SCA) occurs in 0.4% of the general population and up to 6% or more of at-risk groups each year. Early CPR and defibrillation improves SCA outcomes but access to automatic external defibrillators (AEDs) remains limited. Methods: Markov models were used to evaluate the cost-effectiveness of a portable SMART (SMall AED for Rapid Treatment of SCA) approach to early SCA management over a life-time horizon in at-risk and not at-risk populations. Simulated patients (n = 600,000) who had not received an implantable cardioverter defibrillator (ICD) were randomized to a SMART device with CPR prompts or non-SMART approaches. Annual SCA risk was varied from 0.2 to 3.5%. Analysis was performed in a US economy from both societal (SP) and healthcare (HP) perspectives to evaluate the number of SCA fatalities prevented by SMART, and SMART cost-effectiveness at a threshold of $100,000/Quality Adjusted Life Year (QALY). Results: A SMART approach was cost-effective when annual SCA risk exceeded 1.51% (SP) and 1.62% (HP). The incremental cost-effectiveness ratios (ICER) were $95,251/QALY (SP) and $100,797/QALY (HP) at a 1.60% SCA annual risk. At a 3.5% annual SCA risk, SMART was highly cost-effective from both SP and HP [ICER: $53,925/QALY (SP), $59,672/QALY (HP)]. In microsimulation, SMART prevented 1,762 fatalities across risk strata (1.59% fatality relative risk reduction across groups). From a population perspective, SMART could prevent at least 109,839 SCA deaths in persons 45 years and older in the United States. Conclusions and Relevance: A SMART approach to SCA prophylaxis prevents fatalities and is cost-effective in patients at elevated SCA risk. The availability of a smart-phone enabled pocket-sized AED with CPR prompts has the potential to greatly improve population health and economic outcomes.

Text-mining of PubMed abstracts by natural language processing to create a public knowledge base on molecular mechanisms of bacterial enteropathogens.

BACKGROUND: The Enteropathogen Resource Integration Center (ERIC; http://www.ericbrc.org) has a goal of providing bioinformatics support for the scientific community researching enteropathogenic bacteria such as Escherichia coli and Salmonella spp. Rapid and accurate identification of experimental conclusions from the scientific literature is critical to support research in this field. Natural Language Processing (NLP), and in particular Information Extraction (IE) technology, can be a significant aid to this process. DESCRIPTION: We have trained a powerful, state-of-the-art IE technology on a corpus of abstracts from the microbial literature in PubMed to automatically identify and categorize biologically relevant entities and predicative relations. These relations include: Genes/Gene Products and their Roles; Gene Mutations and the resulting Phenotypes; and Organisms and their associated Pathogenicity. Evaluations on blind datasets show an F-measure average of greater than 90% for entities (genes, operons, etc.) and over 70% for relations (gene/gene product to role, etc). This IE capability, combined with text indexing and relational database technologies, constitute the core of our recently deployed text mining application. CONCLUSION: Our Text Mining application is available online on the ERIC website (http://www.ericbrc.org/portal/eric/articles). The information retrieval interface displays a list of recently published enteropathogen literature abstracts, and also provides a search interface to execute custom queries by keyword, date range, etc. Upon selection, processed abstracts and the entities and relations extracted from them are retrieved from a relational database and marked up to highlight the entities and relations. The abstract also provides links from extracted genes and gene products to the ERIC Annotations database, thus providing access to comprehensive genomic annotations and adding value to both the text-mining and annotations systems.

Enteropathogen Resource Integration Center (ERIC): bioinformatics support for research on biodefense-relevant enterobacteria.

ERIC, the Enteropathogen Resource Integration Center (www.ericbrc.org), is a new web portal serving as a rich source of information about enterobacteria on the NIAID established list of Select Agents related to biodefense-diarrheagenic Escherichia coli, Shigella spp., Salmonella spp., Yersinia enterocolitica and Yersinia pestis. More than 30 genomes have been completely sequenced, many more exist in draft form and additional projects are underway. These organisms are increasingly the focus of studies using high-throughput experimental technologies and computational approaches. This wealth of data provides unprecedented opportunities for understanding the workings of basic biological systems and discovery of novel targets for development of vaccines, diagnostics and therapeutics. ERIC brings information together from disparate sources and supports data comparison across different organisms, analysis of varying data types and visualization of analyses in human and computer-readable formats.

A new asset for pathogen informatics--the Enteropathogen Resource Integration Center (ERIC), an NIAID Bioinformatics Resource Center for Biodefense and Emerging/Re-emerging Infectious Disease.

ERIC (Enteropathogen Resource Information Center) is one of the National Institute of Allergy and Infectious Diseases (NIAID) Bioinformatics Resource Centers for Biodefense and Emerging/Re-emerging Infectious Disease. ERIC serves as a comprehensive information resource for five related pathogens: Yersinia enterocolitica, Yersinia pestis, diarrheagenic E. coli, Shigella spp., and Salmonella spp. ERIC integrates genomics, proteomics, biochemical and microbiological information to facilitate the interpretation and understanding of ERIC pathogens and select related non-pathogens for the advancement of diagnostics, therapeutics, and vaccines. ERIC (www.ericbrc.org) is evolving to provide state-of-the-art analysis tools and data types, such as genome sequencing, comparative genomics, genome polymorphisms, gene expression, proteomics, and pathways as well as expertly curated community genome annotation. Genome sequence and genome annotation data and a variety of analysis and tools for eight strains of Yersinia enterocolitica and Yersinia pestis pathogens (Yersinia pestis biovars Mediaevalis KIM, Mediaevalis 91001, Orientalis CO92, Orientalis IP275, Antiqua Angola, Antiqua Antiqua, Antiqua Nepal516, and Yersinia enterocolitica 8081) and two strains of Yersinia pseudotuberculosis (Yersinia pseudotuberculosis IP32953 and IP31758) are currently available through the ERIC portal. ERIC seeks to maintain a strong collaboration with the scientific community so that we can continue to identify and incorporate the latest research data, tools, and training to best meet the current and future needs of the enteropathogen research community. All tools and data developed under this NIAID contract will be freely available. Please contact info@ericbrc.org for more information.