Evaluation of Parameters Collected From Routine Data for the Diagnosis of Sepsis and Septic Shock and Their Influence on Time to Diagnosis and Patient Outcome

NCT05383963 · tracked via the Priya Life Science Germany tracker

Sponsor

Charite University, Berlin, Germany

Phase

Observational

Started

2022-07-15

Last updated

2025-12-01

Condition(s) studied

SepsisSeptic Shock

Study summary

Retrospective observational study to develop a Machine Learning Algorithm to evaluate parameters collected from routine data for the diagnosis of sepsis and septic shock and their influence on time to diagnosis and patient outcome.

Eligibility

Sex

ALL

Min age

18 Years

Max age

—

Healthy volunteers

Inclusion Criteria: * age \>= 18 years * ICU stay of \> 24 hours Exclusion Criteria: * none

Primary outcome measure(s)

Sepsis/septic shock — 01.01.2007 -31.12.2021
Development of a machine learning algorithm (MLA) for the prediction of sepsis/septic shock from hospital routine data.

Trial sites (1)

Facility	City	Region	Status
Department of Anesthesiology and Operative Intensive Care Medicine CCM/CVK, Charité - Universitätsmedizin Berlin	Berlin	Germany	Recruiting

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Official registry record

This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.

View NCT05383963 on ClinicalTrials.gov ↗ ← All trials in Germany