AI predicts ICU dangers from old records
NCT ID NCT07317817
First seen Jun 27, 2026 · Last updated Jun 27, 2026
Summary
This study looked at anonymous medical records from over 55,000 past ICU patients to find patterns that could help predict three life-threatening conditions: sepsis (body-wide infection), ARDS (severe lung injury), and acute kidney injury. Researchers used computer models to analyze data like vital signs and lab results from the first 24 hours in the ICU. No new treatments were tested, and no patients were contacted. The goal is to help doctors identify high-risk patients earlier.
This is an AI summary of the original study and may miss details. Read our disclaimer.
Get updates
Get notified about this study
Sign up to get updates when this study changes or when new studies for AKI - ACUTE KIDNEY INJURY are added.
By submitting, you agree to our Terms of use
Conditions
The condition(s) this trial relates to.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.
Contacts and locations
Locations
-
Chongqing Medical University
Chongqing, Chongqing Municipality, 400016, China
More trials for these conditions
Other studies related to the condition(s) this trial covers.
- Can we optimize antibiotic dosing for children with sepsis?
- Could starting feeds sooner shield preterm babies from infection?
- Can brain waves predict thinking problems after sepsis?
- Can tailored nutrition boost recovery in the ICU?
- Blood markers may foretell brain fog after sepsis
- A hidden clue in the fingertips: could a pulse oximeter reading forecast sepsis outcomes?