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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
- Source :
- BMC Infectious Diseases, 18(1). BioMed Central, BMC Infectious Diseases, BMC Infectious Diseases, Vol 18, Iss 1, Pp 1-10 (2018), BMC Infectious Diseases, 18:377. BioMed Central Ltd.
- Publication Year :
- 2018
- Publisher :
- Springer Science and Business Media LLC, 2018.
-
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 (LRTI) 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 LRTI 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 micro-organisms. 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. Trial Registration NCT02025699. Registration Date: January, 1, 2014. Electronic supplementary material The online version of this article (10.1186/s12879-018-3300-9) contains supplementary material, which is available to authorized users.
- Subjects :
- Male
0301 basic medicine
Antibiotic resistance
Antibiotics
Disease
Antimicrobial Stewardship
Study Protocol
0302 clinical medicine
Medical microbiology
Risk Factors
Prospective Studies
030212 general & internal medicine
Child
Respiratory Tract Infections
Respiratory tract infections
Microbiota
Bacterial Infections
Anti-Bacterial Agents
3. Good health
Hospitalization
Infectious Diseases
Virus Diseases
Child, Preschool
Female
Emergency Service, Hospital
Adult
medicine.medical_specialty
Adolescent
medicine.drug_class
030106 microbiology
lcsh:Infectious and parasitic diseases
Host-Parasite Interactions
Diagnosis, Differential
Sepsis
Young Adult
03 medical and health sciences
medicine
Humans
lcsh:RC109-216
Intensive care medicine
business.industry
Infant
Rapid diagnostics
medicine.disease
Omics
Lower respiratory tract infections
Observational study
business
Biomarkers
Subjects
Details
- ISSN :
- 14712334
- Volume :
- 18
- Database :
- OpenAIRE
- Journal :
- BMC Infectious Diseases
- Accession number :
- edsair.doi.dedup.....4b8ade18c7e991d4e640f3de4a989d6b
- Full Text :
- https://doi.org/10.1186/s12879-018-3300-9