AI tool aims to predict and prevent kidney damage after surgery
NCT ID NCT07604662
First seen Jun 24, 2026 · Last updated Jun 27, 2026 · Updated 1 time
Summary
This study tests whether a machine-learning tool built into electronic health records can help doctors reduce kidney injury after surgery. Over 25,000 adults having non-emergency surgery will take part. Doctors are randomly assigned to see the tool's risk prediction, see it with an alert, or not see it at all. The goal is to see if the tool improves care and lowers kidney damage.
What this could mean
Our plain-language read of the trial. This is informational only — not medical advice or a prediction.
- Active substance
- EHR-Embedded AKI Risk Score (a machine-learning tool that predicts kidney injury risk)
- What this could lead to
- If it works, this could show that using a computer tool in medical records helps doctors protect patients' kidneys after surgery, reducing complications.
- What could go wrong
- This is a pragmatic trial testing a decision-support tool, not a new drug. The tool only advises doctors, so its impact depends on whether doctors follow the recommendations. Results may not apply to other hospitals.
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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
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University of California, San Francisco
San Francisco, California, 94158, United States
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