2016
Chair/bedside diagnosis of oral and respiratory tract infections, and identification of antibiotic resistances for personalised monitoring and treatment
Publication
Publication
Global healthcare systems are struggling with the enormous burden associated with infectious diseases, as well as the incessant rise of antimicrobial resistance. In order to adequately address these issues, there is an urgent need for rapid and accurate infectious disease diagnostics. The H2020 project DIAGORAS aims at diagnosing oral and respiratory tract infections using a fully integrated, automated and user-friendly platform for physicians' offices, schools, elderly care units, community settings, etc. Oral diseases (periodontitis, dental caries) will be detected via multiplexed, quantitative analysis of salivary markers (bacterial DNA and host response proteins) for early prevention and personalised monitoring. Respiratory Tract Infections will be diagnosed by means of DNA/RNA differentiation so as to identify their bacterial or viral nature. Together with antibiotic resistance screening on the same platform, a more efficient treatment management is expected at the point-of-care. At the heart of DIAGORAS lies a centrifugal microfluidic platform (LabDisk and associated processing device) integrating all components and assays for a fully automated analysis. The project involves an interface with a clinical algorithm for the comprehensive presentation of results to end-users, thereby increasing the platform's clinical utility. DIAGORAS' performance will be validated at clinical settings and compared with gold standards.
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| doi.org/10.3233/978-1-61499-653-8-61, hdl.handle.net/1765/96668 | |
| Studies in Health Technology and Informatics | |
| Organisation | Erasmus MC: University Medical Center Rotterdam |
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Mitsakakis, K., Stumpf, F. (Fabian), Strohmeier, O. (Oliver), Klein, V. (Vanessa), Mark, D. (Daniel), Von Stetten, F. (Felix), … Zengerle, R. (Roland). (2016). Chair/bedside diagnosis of oral and respiratory tract infections, and identification of antibiotic resistances for personalised monitoring and treatment. In Studies in Health Technology and Informatics. doi:10.3233/978-1-61499-653-8-61 |
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