Bisoprolol compared with carvedilol and metoprolol succinate in the treatment of patients with chronic heart failure

© 2017, Springer-Verlag Berlin Heidelberg. Aims: Beta-blockers are recommended for the treatment of chronic heart failure (CHF). However, it is disputed whether beta-blockers exert a class effect or whether there are differences in efficacy between agents. Methods and results: 6010 out-patients with stable CHF and a reduced left ventricular ejection fraction prescribed either bisoprolol, carvedilol or metoprolol succinate were identified from three registries in Norway, England, and Germany. In three separate matching procedures, patients were individually matched with respect to both dose equivalents and the respective propensity scores for beta-blocker treatment. During a follow-up of 26,963 patient-years, 302 (29.5%), 637 (37.0%), and 1232 (37.7%) patients died amongst those prescribed bisoprolol, carvedilol, and metoprolol, respectively. In univariable analysis of the general sample, bisoprolol and carvedilol were both associated with lower mortality as compared with metoprolol succinate (HR 0.80, 95% CI 0.71–0.91, p  <  0.01, and HR 0.86, 95% CI 0.78–0.94, p  <  0.01, respectively). Patients prescribed bisoprolol or carvedilol had similar mortality (HR 0.94, 95% CI 0.82–1.08, p = 0.37). However, there was no significant association between beta-blocker choice and all-cause mortality in any of the matched samples (HR 0.90; 95% CI 0.76–1.06; p = 0.20; HR 1.10, 95% CI 0.93–1.31, p = 0.24; and HR 1.08, 95% CI 0.95–1.22, p = 0.26 for bisoprolol vs. carvedilol, bisoprolol vs. metoprolol succinate, and carvedilol vs. metoprolol succinate, respectively). Results were confirmed in a number of important subgroups. Conclusion: Our results suggest that the three beta-blockers investigated have similar effects on mortality amongst patients with CHF

Information retrieval and text mining technologies for chemistry

Efficient access to chemical information contained in scientific literature, patents, technical reports, or the web is a pressing need shared by researchers and patent attorneys from different chemical disciplines. Retrieval of important chemical information in most cases starts with finding relevant documents for a particular chemical compound or family. Targeted retrieval of chemical documents is closely connected to the automatic recognition of chemical entities in the text, which commonly involves the extraction of the entire list of chemicals mentioned in a document, including any associated information. In this Review, we provide a comprehensive and in-depth description of fundamental concepts, technical implementations, and current technologies for meeting these information demands. A strong focus is placed on community challenges addressing systems performance, more particularly CHEMDNER and CHEMDNER patents tasks of BioCreative IV and V, respectively. Considering the growing interest in the construction of automatically annotated chemical knowledge bases that integrate chemical information and biological data, cheminformatics approaches for mapping the extracted chemical names into chemical structures and their subsequent annotation together with text mining applications for linking chemistry with biological information are also presented. Finally, future trends and current challenges are highlighted as a roadmap proposal for research in this emerging field.A.V. and M.K. acknowledge funding from the European Community’s Horizon 2020 Program (project reference: 654021 - OpenMinted). M.K. additionally acknowledges the Encomienda MINETAD-CNIO as part of the Plan for the Advancement of Language Technology. O.R. and J.O. thank the Foundation for Applied Medical Research (FIMA), University of Navarra (Pamplona, Spain). This work was partially funded by Consellería de Cultura, Educación e Ordenación Universitaria (Xunta de Galicia), and FEDER (European Union), and the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684). We thank Iñigo Garciá -Yoldi for useful feedback and discussions during the preparation of the manuscript.info:eu-repo/semantics/publishedVersio