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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.

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.

SUBMITTER: van Houten CB

PROVIDER: S-EPMC6081806 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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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.

van Houten C B CB Oved K K Eden E E Cohen A A Engelhard D D Boers S S Kraaij R R Karlsson R R Fernandez D D Gonzalez E E Li Y Y Stubbs A A Moore E R B ERB Hays J P JP Bont L J LJ

BMC infectious diseases 20180807 1

<h4>Background</h4>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 patien ...[more]

PMID: 30086729

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Project description:Respiratory tract infections account for high morbidity and mortality around the world. Fragile patients are at high risk of developing complications such as pneumonia and may die from it. Limited information is available on the extent of the circulation of respiratory viruses in the hospital setting. Most knowledge relates to influenza viruses (FLU) but several other viruses produce flu-like illness. The study was conducted at the University Hospital Policlinico Tor Vergata, Rome, Italy. Clinical and laboratory data from hospitalized patients with respiratory tract infections during the period October 2016-March 2019 were analysed. The retrospective analysis included 17 viral agents detected by FilmArray test and clinical data from medical records and hospital discharge sheets. Models were adjusted for relevant confounders such as clinical severity and risk of death, socio-demographic characteristics and surgical procedures. From a total of 539 specimens analysed, 180 (33.39%) were positive for one or more respiratory viruses. Among them, 83 (46.1 %) were positive for influenza viruses (FLU), 36 (20%) rhino/enteroviruses (RHV/EV), 17 (9.44%) human coronaviruses (HCOV-229E, -HKU1, -NL63, and -OC43), 17 (9.44%) respiratory syncytial virus, 15 (8.33%) human metapneumovirus (HMPV), 8 (4.44%) parainfluenza viruses (PIV) and 4 (2.22%) adenoviruses (ADV). The distribution of viral agents varied across age groups and month of detection. The positive specimens were from 168 patients [102 M, 66 F; median age (range): 64 years (19-93)]. Overall, 40% of them had a high-grade clinical severity and a 27% risk of death; 27 patients died and 22 of them (81.5%) had received a clinical diagnosis of pneumonia. Respiratory viral infections may have a severe course and a poor prognosis in hospitalized patients, due to underlying comorbidities. Monitoring the circulation of respiratory viruses in hospital settings is important to improve diagnosis, prevention and treatment.

Dataset Information

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.

Publications

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.

Similar Datasets

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