Evidence map›Paper›PMID 30086729›Full record

Observational studyBMC infectious diseases2018

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.

C B van Houten, K Oved, E Eden, A Cohen, D Engelhard, S Boers, R Kraaij, R Karlsson, D Fernandez, E Gonzalez and 5 more

Registry-linked trialOpen access · goldAbstract readMulticenter StudyObservational Study
In one paragraph

Observational study in BMC infectious diseases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02025699 (Observational Multi-center, Prospective Study to Characterize Novel pathogen-and Host-related Factors in Hospitalized Patients and Patients on the Emergency Department Presenting With Lower Respiratory Tract Infections and/or Sepsis.), which is not on this map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT02025699 completednot on this map

Observational Multi-center, Prospective Study to Characterize Novel pathogen-and Host-related Factors in Hospitalized Patients and Patients on the Emergency Department Presenting With Lower Respiratory Tract Infections and/or Sepsis.

TypeobservationalSponsorMeMed Diagnostics Ltd.Ran2014 to 2016Enrolled1,200ConditionsLRTI, Sepsis, Fungal Infections, Bacteremia
3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Observational
  9. Review
  10. Antibiotic misuse in respiratory tract infections in children and adults-a prospective, multicentre study (TAILORED Treatment).European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2019
    Article
  11. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 6 institutions in 4 countries.

C B van HoutenDivision of Paediatric Immunology and Infectious Diseases, University Medical Centre Utrecht, Utrecht University, Office KC.03.063.0, P.O. Box 85090, 3508 AB, Utrecht, The Netherlands.ORCID 0000-0001-6808-1300
K OvedMeMed, Tirat Carmel, Israel.
E EdenMeMed, Tirat Carmel, Israel.
A CohenMeMed, Tirat Carmel, Israel.
D EngelhardDivision of Paediatric Infectious Disease Unit, Hadassah-Hebrew University Medical Centre, Jerusalem, Israel.
S BoersDepartment of Medical Microbiology and Infectious Diseases, Erasmus University Medical Centre (Erasmus MC), Rotterdam, the Netherlands.
R KraaijDepartment of Internal Medicine, Erasmus University Medical Centre (Erasmus MC), Rotterdam, the Netherlands.
R KarlssonDepartment of Infectious Diseases, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
D FernandezNoray Bioinformatics, Derio, Spain.
E GonzalezNoray Bioinformatics, Derio, Spain.
Y LiDepartment of Pathology, Clinical Bioinformatics Unit, Erasmus University Medical Centre (Erasmus MC), Rotterdam, the Netherlands.
A StubbsDepartment of Pathology, Clinical Bioinformatics Unit, Erasmus University Medical Centre (Erasmus MC), Rotterdam, the Netherlands.
E R B MooreUniversity of Gothenburg, Gothenburg, Sweden.
J P HaysDepartment of Medical Microbiology and Infectious Diseases, Erasmus University Medical Centre (Erasmus MC), Rotterdam, the Netherlands.
L J BontDivision of Paediatric Immunology and Infectious Diseases, University Medical Centre Utrecht, Utrecht University, Office KC.03.063.0, P.O. Box 85090, 3508 AB, Utrecht, The Netherlands. l.bont@umcutrecht.nl.
Erasmus MC · NLMeMed (Israel) · ILNoray Bioinformatics (Spain) · ESUniversity of Gothenburg · SEUtrecht University · NLHadassah Medical Center · IL

Funding

EU's Seventh Framework Programme F3-602860-2013
6 · The paper itself

Abstract

backgroundThe 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.

methodsA 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 registrationNCT02025699 . Registration Date: January, 1, 2014.

Indexed as

AdolescentAdultAnti-Bacterial AgentsAntimicrobial StewardshipBacterial InfectionsBiomarkersChildChild, PreschoolDiagnosis, DifferentialEmergency Service, HospitalFemaleHospitalizationHost-Parasite InteractionsHumansInfantMaleAnti-Bacterial AgentsBiomarkersAntibiotic resistanceLower respiratory tract infectionsRapid diagnosticsSepsis

Identifiers

PMID30086729
PMCPMC6081806
OpenAlexW2887931699

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.