Molecular Diagnosis and Risk Stratification of Sepsis (MARS)
Background: Sepsis is a major cause of in-hospital morbidity and mortality. Current tools available to the clinician to initiate therapy of patients with sepsis mainly comprise of symptom classification systems and culture techniques, which provide aspecific and slow information.
Objective: The ultimate goal of this program is to assist the physician at the bedside in tailoring the treatment of an individual patient suffering from sepsis by generating rapid molecular information about the causative pathogen and the host response.
Deliverables: Rapid tests ("sample-in-result-out") that can be used by health care personnel at or close to the bedside and that provide rapid information (within two hours) about the presence or absence of sepsis, the causative pathogen and the risk of the individual patient for sepsis complications and death.
Design: The program is organized into four Work Packages (WPs) along a clinical, discovery and technology platform. In WP1 two university hospitals will enroll 7500 patients admitted to the Intensive Care Unit during the first 3 years of the project; 25% - 40% of these patients will have or will develop sepsis. In WP2 (Pathogen Detection), blood obtained from these patients will be used to develop rapid, fully automated DNA-based bedside tests that identify microorganisms and also provide information about their resistance to antibiotics. In WP3 (Host Response), RNA from blood cells will be analyzed to find novel biomarkers and to develop rapid and easy to perform tests that provide information about the risk profile of the patient. In addition, plasma levels of selected protein biomarkers will be measured for comparison of their value with that of the identified leukocyte molecular signatures. WP4 is responsible for the ICT management of the project. The Clinical Platform (covered by WP1 and WP4) delivers patient data and biological samples to the discovery and technology platforms. The Discovery Platform (covered by WP2 and WP3) uses patient data and biological samples to develop tests for detection of the infectious agent causing sepsis and for stratification of patients according to their risk for sepsis complications, including death. The results generated within the discovery platform will be delivered to the technology platform. The Technology Platform (part of WP2 and WP3) has the specific aim to develop rapid assays that run on a fully automated (micro)fluidics platform that is so easy to operate that it can be used in decentralized settings such as (close to) the ICU. The developed assays will make use of the knowledge generated in the discovery platform.
|Study Type:||Observational [Patient Registry]|
|Study Design:||Observational Model: Cohort
Time Perspective: Prospective
|Target Follow-Up Duration:||1 Year|
|Official Title:||Molecular Diagnosis and Risk Stratification of Sepsis|
- Molecular information about causative pathogens and the host response in patients with sepsis [ Time Frame: One year ] [ Designated as safety issue: No ]
- Stratification of septic patients by severity and type of immune response to infection [ Time Frame: Five years ] [ Designated as safety issue: No ]
Biospecimen Retention: Samples With DNA
Whole blood, plasma, RNA, DNA.
|Study Start Date:||January 2011|
|Estimated Study Completion Date:||June 2014|
|Estimated Primary Completion Date:||June 2014 (Final data collection date for primary outcome measure)|
Please refer to this study by its ClinicalTrials.gov identifier: NCT01905033
|Contact: Tom van der Poll, Prof.||+email@example.com|
|Academic Medical Center||Recruiting|
|Amsterdam, Noord-Holland, Netherlands, 1105 AZ|
|Contact: Tom van der Poll, Prof.|
|Principal Investigator: Tom van der Poll, Prof.|
|University Medical Center Utrecht||Recruiting|
|Utrecht, Netherlands, 3584 CX|
|Contact: Marc J Bonten, Prof. firstname.lastname@example.org|
|Principal Investigator: Marc J. Bonten, Prof.|
|Principal Investigator:||Tom van der Poll, Prof.||Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)|