Personalized Swiss Sepsis Study (PSSS_digital)

University Hospital Basel

Status: Enrolling

Conditions: Sepsis

Treatments: 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

Funder types: Other

Identifiers

NCT04130789

2019-01088 qu18Egli2;

Details and patient eligibility

About

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).

Enrollment: 17,500 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

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.

Trial design

17,500 participants in 2 patient groups

patients with sepsis (cases)

Description:

patients who developed or were admitted with sepsis to the ICU (cases)

Treatment:

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

Other: compare data patterns by data-driven algorithms to determine sepsis

patients without sepsis (controls)

Description:

patients who did not develop sepsis (controls).

Treatment:

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

Other: compare data patterns by data-driven algorithms to determine sepsis