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Chair/bedside diagnosis of oral and respiratory tract infections, and identification of antibiotic resistances for personalised monitoring and treatment


Mitsakakis, Konstantinos; Stumpf, Fabian; et al; Tawakoli, Pune N; Wegehaupt, Florian J; Attin, Thomas; Bostanci, Nagihan; Bao, Kai; Belibasakis, Georgios N (2016). Chair/bedside diagnosis of oral and respiratory tract infections, and identification of antibiotic resistances for personalised monitoring and treatment. In: Maglaveras, Nicos; Gizeli, Electra. pHealth 2016. Amsterdam: I O S Press, 61-66.

Abstract

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.

Abstract

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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Additional indexing

Item Type:Book Section, refereed, original work
Communities & Collections:04 Faculty of Medicine > Center for Dental Medicine > Clinic of Conservative and Preventive Dentistry
04 Faculty of Medicine > Center for Dental Medicine > Institute of Oral Biology
Dewey Decimal Classification:610 Medicine & health
Scopus Subject Areas:Physical Sciences > Biomedical Engineering
Health Sciences > Health Informatics
Health Sciences > Health Information Management
Language:English
Date:2016
Deposited On:04 Jan 2017 15:32
Last Modified:16 May 2024 03:39
Publisher:I O S Press
Series Name:Studies in Health Technology and Informatics
Number:224
ISSN:0926-9630
ISBN:978-1-61499-652-1 (print) | 978-1-61499-653-8 (online)
OA Status:Green
Publisher DOI:https://doi.org/10.3233/978-1-61499-653-8-61
PubMed ID:27225554
  • Content: Accepted Version
  • Language: English