Skip to main content
OpenTrials
Recruiting

NCT Number: NCT05383963

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

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.

Recruiting

Interested in participating?

Request Info

Key information

Conditions

Sepsis Infections Inflammation Pathologic Processes Pathological Conditions, Signs and Symptoms Septic Shock Shock Shock, Septic Systemic Inflammatory Response Syndrome

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Department of Anesthesiology and Operative Intensive Care Medicine CCM/CVK, Charité - Universitätsmedizin Berlin

Berlin, 13353, Germany

Location status: Recruiting

Location contact

Andreas Edel, MD

SUB_INVESTIGATOR

Carolin Steffen, MD

SUB_INVESTIGATOR

Claudia Spies, MD, Prof.

CONTACT

[email protected]

+49 30 450 55 11 02

Claudia Spies, MD, Prof.

PRINCIPAL_INVESTIGATOR

Fabian Schreiber, MD

SUB_INVESTIGATOR

Oliver Kumpf, MD

SUB_INVESTIGATOR

About this study

Retrospective routine data from the medical records of the department of anesthesiology and operative intensive care from 01. 01. 2007 to 31. 12. 2021 are analyzed in digital form.

The first step is the development of a machine learning algorithm (MLA). This MLA will be validated and analyzed for his predictive value with regard to early diagnosis of sepsis/septic shock depending on the conceptual value of detection variables (Sepsis-3 vs. SIRS). Further analysis will focus on improvement of accuracy for the MLA and the effect of these detection variables on quality of treatment processes and also on economic consequences like cost and revenue.

Timeline:

  • Conception and development of the ML Algorithm (6 months)
  • Identification and diagnostic validation of sepsis patients (6 months)
  • Secondary analyses (36 months)

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • age >= 18 years
  • ICU stay of > 24 hours

Exclusion criteria

  • none

Treatment and study plan

Primary outcomes

  1. Sepsis/septic shock

    Time frame: 01.01.2007 -31.12.2021

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

Secondary outcomes

  1. Predictive accuracy

    Time frame: 01.01.2007 -31.12.2021

    Evaluation of the predictive accuracy (= predictive value) of the respective sepsis diagnostic algorithm (i.e. comparison of the concepts SIRS and Sepsis-3)

  2. Diagnostic accuracy

    Time frame: 01.01.2007 -31.12.2021

    Identification of additional variables for diagnostic accuracy (laboratory values, clinical parameters and vital-sign monitor parameters and other relevant health data

  3. Performance indicators

    Time frame: 01.01.2007 -31.12.2021

    Evaluation of performance indicators of clinical routine processes (Intensive care quality indicators)

  4. Case costs

    Time frame: 01.01.2007 -31.12.2021

    Case costs related to hospitalization

  5. Revenues

    Time frame: 01.01.2007 -31.12.2021

    Revenues related to hospitalization

Study contacts

Contact information is provided by the study sponsor or research team.

Claudia Spies, MD, Prof.

CONTACT

[email protected]

+49 30 450 55 11 02

Sponsors and collaborators

Lead sponsor

Charite University, Berlin, Germany

Other

Registry information

Official study title

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 (QUICK-SEPSIS)

Important dates

Study start
2022
Primary completion
2026
Study completion
2027
First posted
May 20, 2022
Registry last updated
Dec 1, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Related clinical trials

Published trials that share one or more normalized conditions with this study.