Personalized Swiss Sepsis Study (PSSS_digital)

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

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).

Study Overview

• Status: Recruiting
• Conditions: Sepsis
• Intervention / Treatment: Other: compare data patterns by data-driven algorithms to determine sepsis; Other: compare data patterns by data-driven algorithms to predict sepsis-related mortality

• Study Type: Observational
• Enrollment (Anticipated): 17500

Contacts and Locations

• Study Contact: Name: Adrian Egli, PD Dr.; Phone Number: +41 61 556 5749; Email: adrian.egli@usb.ch

Study Locations

• Switzerland
  • Basel, Switzerland, 4031
    • Recruiting
    • Clinical Microbiology, University Hospital Basel
    • Contact: Adrian Egli, PD Dr. med; Phone Number: +41 61 556 5749; Email: adrian.egli@usb.ch
  • Basel, Switzerland, 4031
    • Recruiting
    • Infectious Diseases and Hospital Epidemiology, University Hospital Basel
    • Contact: Manuel Battegay, Prof Dr med
  • Basel, Switzerland, 4031
    • Recruiting
    • Medical Intensive Care Unit; University Hospital Basel
    • Contact: Stephan Marsch, Prof. Dr. MD
  • Basel, Switzerland, 4031
    • Recruiting
    • Surgical Intensive Care Unit, University Hospital Basel
    • Contact: Martin Siegemund, Prof. Dr. MD
  • Bern, Switzerland, 3001
    • Recruiting
    • Institute for Infectious Diseases, University of Bern
    • Contact: Stephen Leib, Prof. Dr. MD
  • Bern, Switzerland, 3010
    • Recruiting
    • Division Infectious Diseases, University Hospital Bern
    • Contact: Hansjakob Furrer, Prof.Dr.med
  • Bern, Switzerland, 3010
    • Recruiting
    • Intensive Care Medicine, University Hospital Bern
    • Contact: Stephan Jakob, Prof. Dr. MD
  • Geneva, Switzerland, 1205
    • Recruiting
    • Division Bacteriology Laboratory, University Hospital Geneva
    • Contact: Jacques Schrenzel, Prof Dr med
  • Geneva, Switzerland, 1205
    • Recruiting
    • Division Infectious Diseases, University Hospital Geneva
    • Contact: Laurent Kaiser, Prof. Dr. MD
  • Geneva, Switzerland, 1205
    • Recruiting
    • Intensive Care Medicine, University Hospital Geneva
    • Contact: Jérôme Pugin, Prof. Dr. MD
  • Lausanne, Switzerland, 1011
    • Recruiting
    • Division Intensive Care Medicine, University Hospital Lausanne
    • Contact: Philippe Eckert, Prof. Dr. MD
  • Lausanne, Switzerland, 1011
    • Recruiting
    • Institute of Microbiology, University Hospital Lausanne
    • Contact: Gilbert Greub, Prof. Dr. MD
  • Lausanne, Switzerland, 1011
    • Recruiting
    • Service Infectious Diseases, University Hospital Lausanne
    • Contact: Thierry Calandra, Prof. Dr. MD
  • Zürich, Switzerland, 8006
    • Not yet recruiting
    • Institute for Medical Microbiology, University Hospital Zurich
    • Contact: Reinhard Zbinden, Prof. Dr. MD
  • Zürich, Switzerland, 8091
    • Not yet recruiting
    • Division Infectious Diseases, University Hospital Zurich
    • Contact: Annelies Zinkernagel, Prof. Dr. MD
  • Zürich, Switzerland, 8091
    • Not yet recruiting
    • Institute for Intensive Medicine, University Hospital Zurich
    • Contact: Reto Schüpbach, Prof. Dr. MD

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Probability Sample

Study Population

ICU patients on a Swiss University Hospital ICU from 01.08.2019

Description

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.

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
patients with sepsis (cases); patients who developed or were admitted with sepsis to the ICU (cases)	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
patients without sepsis (controls); patients who did not develop sepsis (controls).	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

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
sepsis-related mortality (sensitivity)	Algorithm to predict sepsis-related mortality (sensitivity)	time- series data collected from hospital entry until maximum 12 months after hospital exit (no exact time point specified)
sepsis-related mortality (specificity)	Algorithm to predict sepsis-related mortality (specificity)	time- series data collected from hospital entry until maximum 12 months after hospital exit (no exact time point specified)
Determination of sepsis	Algorithm to determine sepsis at an early stage (at least 12 hours before classical definitions)	time- series data collected from hospital entry until hospital exit; an average of 1 month (no exact time point specified)

Collaborators and Investigators

• Sponsor: University Hospital, Basel, Switzerland
• Collaborators: Swiss Personalized Health Network (SPHN); Personalized Health and Related Technologies (PHRT) initiative of ETH Zürich
• Investigators: Principal Investigator: Adrian Egli, PD Dr., Clinical Microbiology, University Hospital Basel

Study record dates

Study Major Dates

• Study Start (Actual): November 15, 2019
• Primary Completion (Anticipated): June 1, 2022
• Study Completion (Anticipated): June 1, 2023

Study Registration Dates

• First Submitted: October 15, 2019
• First Submitted That Met QC Criteria: October 16, 2019
• First Posted (Actual): October 17, 2019

Study Record Updates

• Last Update Posted (Actual): August 4, 2021
• Last Update Submitted That Met QC Criteria: August 3, 2021
• Last Verified: August 1, 2021

More Information

Terms related to this study

• Keywords: machine learning; clinical data warehouse (CDWH); data-driven algorithms; multi-dimensional modelling
• Additional Relevant MeSH Terms: Pathologic Processes; Infections; Systemic Inflammatory Response Syndrome; Inflammation; Sepsis; Toxemia
• Other Study ID Numbers: 2018-01088; qu18Egli2

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No