Molecular Biomarkers for Sepsis

Study Overview
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Brief Summary
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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.

Official Title
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Prospective Study to Discover New Biomarkers for Early Detection of Sepsis and Prediction of Sepsis-related Mortality in Patients With Severe Community Acquired Pneumonia (sCAP)

Conditions
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Sepsis, Severe Community-acquired Pneumonia (sCAP), Infection, Bacterial

Intervention / Treatment
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* Other: compare data patterns by data-driven algorithms to determine sepsis
* Other: compare data patterns by data-driven algorithms to predict sepsis-related mortality


Participation Criteria
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Eligibility Criteria
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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.

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| patients with severe community acquired pneumonia (cases)<br>Cases: Patients with severe community acquired pneumonia with required ICU admission. | Other: compare data patterns by data-driven algorithms to determine sepsis<br>* compare data patterns by data-driven algorithms including machine learning and multi-dimensional modelling to reliably determine sepsis<br>Other: compare data patterns by data-driven algorithms to predict sepsis-related mortality<br>* compare data patterns by data-driven algorithms including machine learning and multi-dimensional modelling to to predict sepsis-related mortality<br>|
| patients without pneumonia or sepsis (controls)<br>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. | Other: compare data patterns by data-driven algorithms to determine sepsis<br>* compare data patterns by data-driven algorithms including machine learning and multi-dimensional modelling to reliably determine sepsis<br>Other: compare data patterns by data-driven algorithms to predict sepsis-related mortality<br>* compare data patterns by data-driven algorithms including machine learning and multi-dimensional modelling to to predict sepsis-related mortality<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Detection of sepsis | 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). | within 7 days after study inclusion | 
| Sepsis related mortality | Prediction of sepsis related mortality (with >80% sensitivity and specificity at least 24h prior to event) | within 7 days after study inclusion | 
| Time to sepsis detection (minutes after Intensive Care Unit (ICU) admission) | Time to sepsis detection (minutes after ICU admission) based on machine learning | within 7 days after study inclusion | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Community-acquired Pneumonia, biomarker, clinical data warehouse (CDWH), machine learning, data-driven algorithms, multi-dimensional modelling, sepsis-related mortality, Streptococcus pneumoniae