Machine learning prediction of acute kidney injury after non-cardiac surgery
Official title: A Machine Learning Prediction Model for Postoperative Acute Kidney Injury in Non-Cardiac Surgery Patients: Development, Validation, and the Incremental Value of Frailty Assessment
Run by Zhongda Hospital · NCT07030166 · Data updated 2026-11-12
This project will try a computer-based model to predict which adults are at risk of acute kidney injury after non-cardiac surgery.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 10000 (estimated) |
| Sponsor | Zhongda Hospital Academic / other |
| Locations | 1 site (Nanjing) |
| Status | Recruiting |
| Started | July 1, 2025 |
| Main results expected | December 31, 2026 |
| Study ends | December 31, 2026 |
| Registry record updated | April 2, 2026 |
| Trial ID | NCT07030166 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates are adults (≥18) undergoing non-cardiac surgery at the participating hospital who have both pre- and postoperative serum creatinine measurements.
✕Probably not a fit
Patients with recent dialysis-dependent end-stage renal disease, baseline creatinine ≥4.5 mg/dL, preoperative AKI within 7 days, renal surgery, missing creatinine measurements, or operations under 2 hours are unlikely to benefit.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational project develops and validates a machine-learning model to predict acute kidney injury (AKI) after non-cardiac surgery using hospital electronic medical records. Retrospective data from adult patients who had non-cardiac surgery between July 2015 and June 2025 will serve as the development set, and prospective data collected from July 2025 to February 2026 will provide temporal external validation. The model will include routine clinical variables and add a frailty assessment as a new predictor to measure its incremental value. No interventions are applied; inclusion requires pre- and postoperative serum creatinine measurements and several renal- and surgery-related exclusions are enforced.
Why it matters
Potential benefit: If successful, the model could identify high-risk patients so clinicians can apply preventive measures to reduce the chance or severity of postoperative AKI.
How similar studies have gone: Previous machine-learning models for postoperative AKI have shown promising results in retrospective cohorts, but externally validated models—especially those incorporating frailty—are still limited.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * 18 years old or above * Undergo non-cardiac surgery Exclusion Criteria: * At least one measurement of serum creatinine (SCr) was not conducted before and after the operation * End-stage renal disease (ESRD) that has received dialysis within the past year * Baseline SCr ≥ 4.5 mg/dl (because the clinical criteria for AKI based on elevated SCr may not be applicable to these patients) * Acute kidney injury occurred within 7 days before the operation * The surgical procedure is renal surgery * The operation time is less than 2 hours
Where it's running
-
Zhongda Hospital Southeast University
Nanjing, China Recruiting
Study contacts
- Study coordinator: Yue Lan Zhu
- Email: zhulanyue1993@126.com
- Phone: +8618795969178
Similar studies
Other studies for the same condition or treatment. Recruiting studies are listed first.
-
Sodium nitrate to prevent contrast-associated acute kidney injury
This pilot will test whether taking sodium nitrate around the time of a coronary angiogram or contrast-enhanced CT can prevent contrast-associated acute kidney injury in people at high risk.
-
Remote Ischemic Preconditioning at Different Times After Heart Valve Surgery
This study tests whether applying brief, controlled blood-flow restrictions to a limb at different times after heart valve surgery can help protect organs and reduce complications like kidney injury.
-
Clinical decision support to help consider SGLT2 inhibitors after AKI in type 2 diabetes
This pilot test checks if a CDS message given to clinicians can help decide whether to consider SGLT2 inhibitors for adults with type 2 diabetes who recently had acute kidney injury.
-
Biomarkers to predict CSA-AKI risk before heart surgery
This study tests new biomarkers to see if they can predict CSA-AKI risk in adults undergoing cardiovascular surgery.
-
Reducing Endotoxin Burden in Septic Shock Patients on CRRT with the oXiris Filter
This trial tests whether using the oXiris hemofilter during continuous kidney replacement helps lower endotoxin levels in adults with septic shock who need CRRT.
-
Perioperative GFR Monitoring to Predict CSA-AKI and CA-AKI
This study tests whether perioperative transcutaneous fluorescence GFR measurements can predict CSA-AKI or CA-AKI in adults undergoing cardiovascular procedures or iodine contrast exposure.
How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.