Molecular Biomarkers for Sepsis

Terminated

• Conditions: Sepsis; Severe Community-acquired Pneumonia (sCAP); Infection, Bacterial
• Interventions: Other: compare data patterns by data-driven algorithms to determine sepsis; Other: compare data patterns by data-driven algorithms to predict sepsis-related mortality

• Registration Number: NCT04280354
• Lead Sponsor: University Hospital, Basel, Switzerland

Brief Summary

This multi-center observational case-control study in Intensive Care Unit (ICU) patients is to identify novel biomarkers allowing to recognize severe community acquired pneumonia (sCAP) -associated sepsis at an earlier stage and predict sepsis-related mortality. Patients with sCAP (cases) will be profoundly characterized over time regarding the development of sepsis and compared with control patients. The mechanisms and influencing factors on the clinical course will be explored with most modern -omics technologies allowing a detailed characterisation. These data will be analysed using machine learning algorithms and multi-dimensional mathematical models.

Detailed Description

Not available

Study Timeline

• Study First Submitted: 2020-02-19
• Study First Submitted QC: 2020-02-19
• Study First Posted: 2020-02-21
• Study Start: 2022-02-16
• Primary Completion: 2022-07-31
• Study Completion: 2022-07-31
• Status Verified: 2024-05
• Last Update Submitted: 2024-05-07
• Last Update Posted: 2024-05-09

Recruitment & Eligibility

• Status: TERMINATED
• Sex: All
• Target Recruitment: 3

Inclusion Criteria

• Admission to the ICU of one of the participating centers.
• Cases: severe community acquired pneumonia with requirement for ICU admission.
• Controls: Clinical phenotype of inflammation not due to suspected sepsis In addition, control patients will be patients with fever >38°C, CRP >100mg/L, no infection focus expected in ≥ 24h.
• All required sample types can most likely be collected within the first 24h visits.
• Expected ICU stay of more than 24h.

Exclusion Criteria

• Admission to the hospital within the prior 14 days.
• Patients with psychosis
• Evidence of a hospital acquired pneumonia.
• One of the following respiratory conditions: Acute exacerbation of chronic obstructive pulmonary disease (COPD) or bronchiectasis, acute severe asthma, aspiration pneumonia, tuberculosis, clinical suspected viral pneumonia without bacterial infection, cardiogenic pulmonary oedema.
• Patients with an acute respiratory distress Syndrome (ARDS).
• Patient which can be managed as outpatients and do not require an ICU.
• Patient where a transmission to another institution is likely within the next 24h.
• Documented rejection of the general consent or participation to research in general.
• Patients with a palliative situation and a life expectancy due to other diseases (e.g. progressed cancer) less than 28 days.

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
patients without pneumonia or sepsis (controls)	compare data patterns by data-driven algorithms to predict sepsis-related mortality	Controls: Clinical phenotype of inflammation not due to suspected sepsis; patients with fever \>38°C, C reactive Protein (CRP) \>100mg/L, no infection focus expected in ≥ 24h.
patients without pneumonia or sepsis (controls)	compare data patterns by data-driven algorithms to determine sepsis	Controls: Clinical phenotype of inflammation not due to suspected sepsis; patients with fever \>38°C, C reactive Protein (CRP) \>100mg/L, no infection focus expected in ≥ 24h.
patients with severe community acquired pneumonia (cases)	compare data patterns by data-driven algorithms to determine sepsis	Cases: Patients with severe community acquired pneumonia with required ICU admission.
patients with severe community acquired pneumonia (cases)	compare data patterns by data-driven algorithms to predict sepsis-related mortality	Cases: Patients with severe community acquired pneumonia with required ICU admission.

Primary Outcome Measures

Name	Time	Method
Detection of sepsis	within 7 days after study inclusion	Sepsis detection based on new discovered digital biomarkers will be compared to classical sepsis-3 criteria (with an increase of the sequential organ failure assessment (SOFA) score of 2 or larger score points).
Time to sepsis detection (minutes after Intensive Care Unit (ICU) admission)	within 7 days after study inclusion	Time to sepsis detection (minutes after ICU admission) based on machine learning
Sepsis related mortality	within 7 days after study inclusion	Prediction of sepsis related mortality (with \>80% sensitivity and specificity at least 24h prior to event)

Trial Locations

Locations (15)

Clinical Bacteriology and Mycology, University Hospital Basel; 🇨🇭 Basel, Switzerland

Infectious Diseases and Hospital Epidemiology, University Hospital Basel; 🇨🇭 Basel, Switzerland

Intensive Care Unit; University Hospital Basel; 🇨🇭 Basel, Switzerland

Institute for Infectious Diseases, University of Bern; 🇨🇭 Bern, Switzerland

Infectious Diseases and Hospital Epidemiology, University Hospital Bern; 🇨🇭 Bern, Switzerland

Intensive Care Unit, University Hospital Bern; 🇨🇭 Bern, Switzerland

Infectious Diseases and Hospital Epidemiology, University Hospital Geneva; 🇨🇭 Geneva,, Switzerland

Clinical Bacteriology, University Hospital Geneva; 🇨🇭 Geneva, Switzerland

Intensive Care Unit, University Hospital Geneva; 🇨🇭 Geneva, Switzerland

Clinical Microbiology, University Hospital Lausanne; 🇨🇭 Lausanne, Switzerland

Infectious Diseases and Hospital Epidemiology , University Hospital Lausanne; 🇨🇭 Lausanne, Switzerland

Intensive Care Unit, University Hospital Lausanne; 🇨🇭 Lausanne, Switzerland

Infectious Diseases and Hospital Epidemiology, University Hospital Zurich; 🇨🇭 Zürich, Switzerland

Institute for Medical Microbiology, University Hospital Zurich; 🇨🇭 Zürich, Switzerland

Intensive Care Unit, University Hospital Zurich; 🇨🇭 Zürich, Switzerland