Clinical Metagenomics of Infective Endocarditis (Meta-ENDO)
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|ClinicalTrials.gov Identifier: NCT03199287|
Recruitment Status : Unknown
Verified June 2017 by Prof. Jacques SCHRENZEL, University Hospital, Geneva.
Recruitment status was: Recruiting
First Posted : June 26, 2017
Last Update Posted : June 26, 2017
Infective endocarditis (IE) is an infection of cardiac valves. IE mainly involves bacteria, more rarely fungi. IE is an uncommon diseases with an estimated incidence of 1-12 cases per 100,000 inhabitants per year. The diagnostic of IE relies on the culture of biological samples (blood cultures and per-operative samples) in the bacteriology laboratory in order to identify the pathogen and its susceptibility to antimicrobials. Nonetheless in about 10% of the cases, the blood cultures remain negative, due to antibiotics taken before harvesting, to non-culturable bacteria or to aseptic phenomena.
Clinical metagenomics is defined as the application of high-throughput sequencing (NGS) followed by a specific bioinformatics analysis to obtain clinical information, i.e. pathogen identification and the prediction of their susceptibility to antimicrobials. The metagenome of a sample (i.e. all the genomes of the organisms present) virtually contains all the information necessary for bacteriological diagnosis: what is the pathogenic bacteria , and to which antibiotics it is susceptible.
Hence, using clinical metagenomics in the context of IE appears seducing in order to overcome the limitations of conventional methods based on culture. Here, we propose to assess the performance of clinical metagenomics in the diagnostic of IE.
|Condition or disease|
|Study Type :||Observational|
|Estimated Enrollment :||100 participants|
|Official Title:||Clinical Metagenomics of Infective Endocarditis|
|Actual Study Start Date :||June 8, 2017|
|Estimated Primary Completion Date :||June 30, 2018|
|Estimated Study Completion Date :||June 30, 2019|
- Diagnostic of IE [ Time Frame: 24 months ]The diagnostic of IE obtained by conventional methods and by clinical metagenomics
- Number of species identified by conventional methods but not by clinical metagenomics [ Time Frame: 24 months ]Number of species identified by conventional methods but not by clinical metagenomics
- Number of species not identified by conventional methods but found in clinical metagenomics [ Time Frame: 24 months ]Number of species not identified by conventional methods but found in clinical metagenomics
- Inference of antibiotic susceptibility [ Time Frame: 24 months ]For each antibiotic, number of patients for whom prediction of bacterial sensitivity agrees with the sensitivity data obtained by conventional methods.
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Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT03199287
|Contact: Jacques Schrenzel, MD||+41 22 372 73 firstname.lastname@example.org|
|Contact: Stéphane Emonet, MD||+41 22 372 73 email@example.com|