RECRUITINGOBSERVATIONAL

Personalized Swiss Sepsis Study

Personalized Swiss Sepsis Study: With Machine Learning and Computational Modelling Towards Personalized Sepsis Management - Discovery of Digital Biomarkers

About This Trial

This multi-center study is to focus on patients with sepsis in Intensive Care Units (ICUs) in order to better understand the complex host-pathogen interaction and clinical heterogeneity associated with sepsis. Understanding this heterogeneity may allow the development of novel diagnostic approaches. Data from patients will be analyzed using state-of-the art analytical algorithms for biomarker discovery including machine learning and multidimensional mathematical modelling to explore the large datasets generated. In order to discover digital biomarkers for the study endpoints a case-control study design will be used to compare data patterns from patients with sepsis (cases) and those without sepsis (controls).

Who May Be Eligible (Plain English)

Who May Qualify: - Patients admitted to an ICU on a Swiss University Hospital. - Patients expected to stay at least 24h on the ICU Inclusion Criteria (cases) - Present at admission to ICU or subsequent development of sepsis 3.0 criteria Inclusion Criteria (controls) - Patients not fulfilling sepsis definition during the ICU stay Who Should NOT Join This Trial: - Decline of general consent or any other negative statement against using data for research. - Patients with a clear elective stay on the ICUs. Always talk to your doctor about whether this trial is right for you.

Original Eligibility Criteria

View original clinical language

Inclusion Criteria: * Patients admitted to an ICU on a Swiss University Hospital. * Patients expected to stay at least 24h on the ICU Inclusion Criteria (cases) * Present at admission to ICU or subsequent development of sepsis 3.0 criteria Inclusion Criteria (controls) * Patients not fulfilling sepsis definition during the ICU stay Exclusion Criteria: * Decline of general consent or any other negative statement against using data for research. * Patients with a clear elective stay on the ICUs.

Treatments Being Tested

OTHER

compare data patterns by data-driven algorithms to determine sepsis

compare data patterns by data-driven algorithms including machine learning and multi-dimensional modelling to reliably determine sepsis

OTHER

compare data patterns by data-driven algorithms to predict sepsis-related mortality

compare data patterns by data-driven algorithms including machine learning and multi-dimensional modelling to to predict sepsis-related mortality

Locations (16)

Clinical Microbiology, University Hospital Basel

Basel, Switzerland

Infectious Diseases and Hospital Epidemiology, University Hospital Basel

Basel, Switzerland

Medical Intensive Care Unit; University Hospital Basel

Basel, Switzerland

Surgical Intensive Care Unit, University Hospital Basel

Basel, Switzerland

Institute for Infectious Diseases, University of Bern

Bern, Switzerland

Division Infectious Diseases, University Hospital Bern

Bern, Switzerland

Intensive Care Medicine, University Hospital Bern

Bern, Switzerland

Division Bacteriology Laboratory, University Hospital Geneva

Geneva, Switzerland

Division Infectious Diseases, University Hospital Geneva

Geneva, Switzerland

Intensive Care Medicine, University Hospital Geneva

Geneva, Switzerland

Division Intensive Care Medicine, University Hospital Lausanne

Lausanne, Switzerland

Institute of Microbiology, University Hospital Lausanne

Lausanne, Switzerland

Service Infectious Diseases, University Hospital Lausanne

Lausanne, Switzerland

Institute for Medical Microbiology, University Hospital Zurich

Zurich, Switzerland

Division Infectious Diseases, University Hospital Zurich

Zurich, Switzerland

Institute for Intensive Medicine, University Hospital Zurich

Zurich, Switzerland