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.

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.

As listed by the trial registrant

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

Contacts and locations

Locations

  • University of California, San Francisco

    San Francisco, California, 94158, United States

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Other studies related to the condition(s) this trial covers.