AI could spot sepsis earlier from routine hospital data

NCT ID NCT05383963

Recruiting now Diagnosis Sponsor: Charite University, Berlin, Germany Source: ClinicalTrials.gov ↗

First seen Jun 27, 2026 · Last updated Jun 27, 2026

Summary

This study looks at using a computer algorithm to quickly diagnose sepsis and septic shock from routine hospital data. Researchers will analyze information from 10,000 ICU patients to see if the algorithm can speed up diagnosis and improve patient outcomes. The goal is to help doctors identify sepsis earlier without extra tests.

What this could mean

Our plain-language read of the trial. This is informational only — not medical advice or a prediction.

What this could lead to: If successful, this could lead to a faster, more accurate way to diagnose sepsis using data already collected in hospitals, potentially saving lives.
What could go wrong: This is an observational study, not a treatment trial. The algorithm may not work as well in real-world settings or may not improve outcomes as hoped.

This is an AI summary of the original study and may miss details. Read our disclaimer.

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Conditions

The condition(s) this trial relates to.

infectious disease with sepsis Sepsis toxic shock syndrome

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

SEPSIS SEPTIC SHOCK

Contacts and locations

Locations

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

Berlin, 13353, Germany

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