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Can AI spot kidney damage before it strikes after heart surgery?

NCT ID NCT07811583

Diagnosis Sponsor: China National Center for Cardiovascular Diseases Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing This study
Running, but no longer taking on new participants.
Completed
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Sep 10, 2026 · Last updated Sep 11, 2026 · Updated 1 time

Summary

Acute kidney injury is a common and serious complication after heart surgery, affecting up to half of patients and raising the risk of death and chronic kidney disease. Researchers are building a machine-learning model that uses perioperative data from 70,000 adults who had cardiovascular surgery to predict who will develop this kidney injury. The goal is a dynamic tool that works across the entire surgical period and different types of operations, so doctors can act earlier to prevent or treat it.

What this could mean

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

Active substance
a machine-learning prediction model built from perioperative patient data
What this could lead to
If it works, doctors could flag patients at high risk of kidney injury before and after heart surgery, opening the door to earlier preventive care.
What could go wrong
This is a retrospective modeling study, not a treatment trial, so the model may not predict accurately in new patients or outside the hospitals where the data came from. It also cannot prove that early prediction improves outcomes.

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

Study facts

What this study's own registry entry says, in plain language.

Participants

About 70,000 people

The number the study aims to enrol. It can still change while the study runs.

Started

Jan 2015

Expected to finish

Dec 2027

An estimate. End dates often move.

Lead sponsor

A government agency

The lead sponsor is a government body.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

The cohort included adult patients who underwent cardiovascular surgery from 2015 to 2025 (Beijing) and from 2022 to 2025 (branch hospital).

Ages

18 years and older

Sex

Anyone

Healthy volunteers

Not accepted

This study is not open to healthy volunteers. The entry requirements below say who it is open to.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Inclusion Criteria: * 1\. Age no less than 18 years old; * 2\. Patients who underwent cardiovascular surgeries at Fuwai Hospital in Beijing from 2015 to 2025 and at Fuwai Hospitals in Central China, Yunnan and Shenzhen from 2022 to 2025; * 3\. At least one blood creatinine test should be conducted within 48 hours after the operation, and at least two blood creatinine tests should be conducted within one week after the operation. Exclusion Criteria: * 1\. Lack of preoperative baseline creatinine; * 2\. Patients who developed AKI before surgery or whose AKI did not recover: The definition of AKI follows the KDIGO 2012 guideline; * 3\. Patients with preoperative creatinine levels exceeding 354umol/L or those in CKD stage 5.

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Conditions

The condition(s) this trial relates to.

acute kidney injury

As listed by the trial registrant

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

Acute kidney injury Cardiovascular surgery Csa-AKI

More trials for these conditions

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