| 11. |
- van Houten, C. B., et al.
(författare)
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Observational multi-centre, prospective study to characterize novel pathogen-and host-related factors in hospitalized patients with lower respiratory tract infections and/or sepsis - the "TAILORED-Treatment" study
- 2018
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Ingår i: BMC Infectious Diseases. - : Springer Science and Business Media LLC. - 1471-2334. ; 18
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Tidskriftsartikel (refereegranskat)abstract
- Background: The emergence and spread of antibiotic resistant micro-organisms is a global concern, which is largely attributable to inaccurate prescribing of antibiotics to patients presenting with non-bacterial infections. The use of 'omics' technologies for discovery of novel infection related biomarkers combined with novel treatment algorithms offers possibilities for rapidly distinguishing between bacterial and viral infections. This distinction can be particularly important for patients suffering from lower respiratory tract infections (LIT(1) and/or sepsis as they represent a significant burden to healthcare systems. Here we present the study details of the TAILORED-Treatment study, an observational, prospective, multi-centre study aiming to generate a multi-parametric model, combining host and pathogen data, for distinguishing between bacterial and viral aetiologies in children and adults with LRTI and/or sepsis. Methods: A total number of 1200 paediatric and adult patients aged 1 month and older with LRT1 and/or sepsis or a non-infectious disease are recruited from Emergency Departments and hospital wards of seven Dutch and Israeli medical centres. A panel of three experienced physicians adjudicate a reference standard diagnosis for all patients (i.e., bacterial or viral infection) using all available clinical and laboratory information, including a 28-day follow-up assessment. Nasal swabs and blood samples are collected for multi-omics investigations including host RNA and protein biomarkers, nasal microbiota profiling, host genomic profiling and bacterial proteomics. Simplified data is entered into a custom-built database in order to develop a multi-parametric model and diagnostic tools for differentiating between bacterial and viral infections. The predictions from the model will be compared with the consensus diagnosis in order to determine its accuracy. Discussion: The TAILORED-Treatment study will provide new insights into the interplay between the host and microorganisms. New host- or pathogen-related biomarkers will be used to generate a multi-parametric model for distinguishing between bacterial and viral infections. This model will be helpful to better guide antimicrobial therapy for patients with LRTI and sepsis. This study has the potential to improve patient care, reduce unnecessary antibiotic prescribing and will contribute positively to institutional, national and international healthcare economics.
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| 12. |
- Cohen, A., et al.
(författare)
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A multifaceted 'omics' approach for addressing the challenge of antimicrobial resistance
- 2015
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Ingår i: Future Microbiology. - : Future Medicine Ltd. - 1746-0913 .- 1746-0921. ; 10:3, s. 365-376
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Tidskriftsartikel (refereegranskat)abstract
- The inappropriate use of antibiotics has severe global health and economic consequences, including the emergence of antibiotic-resistant bacteria. A major driver of antibiotic misuse is the inability to accurately distinguish between bacterial and viral infections based on currently available diagnostic solutions. A multifaceted 'omics' approach that integrates personalized patient data such as genetic predisposition to infections (genomics), natural microbiota composition and immune response to infection (proteomics and transcriptomics) together with comprehensive pathogen profiling has the potential to help physicians improve their antimicrobial prescribing practices. In this respect, the EU has funded a multidisciplinary project (TAILORED-Treatment) that will develop novel omics-based personalized treatment schemes that have the potential to reduce antibiotic consumption, and help limiting the spread of antibiotic resistance.
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