1 The Faculty of Medicine, Aalborg University, VBN2 Department of Clinical Medicine, The Faculty of Medicine, Aalborg University, VBN3 Aalborg University Hospital, The Faculty of Medicine, Aalborg University, VBN4 Klinik Diagnostik, The Faculty of Medicine, Aalborg University, VBN5 Klinisk Mikrobiologi, The Faculty of Medicine, Aalborg University, VBN6 Center for Clinical Epidemiology, Odense University Hospital, DK-5000 Odense C, Denmark7 Department of Clinical Microbiology, Herlev Hospital, Copenhagen University Hospital, Herlev, Denmark.8 Department of Clinical Microbiology, Hvidovre Hospital, Copenhagen University Hospital, Hvidovre, Denmark.9 Department of Clinical Epidemiology, Aalborg Hospital and Aarhus Univeristy Hospital10 Hvidovre Hospital, Hvidovre11 unknown
The Danish Collaborative Bacteraemia Network (DACOBAN) research database includes microbiological data obtained from positive blood cultures from a geographically and demographically well-defined population serviced by three clinical microbiology departments (1.7 million residents, 32% of the Danish population). The database also includes data on comorbidity from the Danish National Patient Registry, vital status from the Danish Civil Registration System, and clinical data on 31% of nonselected records in the database. Use of the unique civil registration number given to all Danish residents enables linkage to additional registries for specific research projects. The DACOBAN database is continuously updated, and it currently comprises 39,292 patients with 49,951 bacteremic episodes from 2000 through 2011. The database is part of an international network of population-based bacteremia registries from five developed countries on three continents. The main purpose of the DACOBAN database is to study surveillance, risk, and prognosis. Sex- and age-specific data on background populations enables the computation of incidence rates. In addition, the high number of patients facilitates studies of rare microorganisms. Thus far, studies on Staphylococcus aureus, enterococci, computer algorithms for the classification of bacteremic episodes, and prognosis and risk in relation to socioeconomic factors have been published.