Using smart computer predictions to prevent kidney injury after heart surgery
Official title: Leveraging Machine Learning for Dynamic Prediction and Mitigation of Acute Kidney Injury after Cardiac Surgery
Funded at Baylor College of Medicine · NIH-11417314 · Data updated 2026-11-12
A machine-learning approach uses routinely collected hospital data to predict who might develop acute kidney injury after heart surgery, so clinicians can act early.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Baylor College of Medicine NIH-funded |
| Lab location | 1 site (Houston, United States) |
| Project start | September 16, 2025 |
| Project end | June 30, 2029 |
| Funding year | 2026 |
| Award (this year) | $586,431 |
| NIH project number | 5R01HL176883-02 |
| Project ID | NIH-11417314 on NIH RePORTER |
Who could benefit from this research
✓Could help
Adults undergoing cardiac surgery who are at risk for acute kidney injury and receive care in hospital ICUs.
✕Less likely to help
Patients not undergoing cardiac surgery or those not in ICU settings may not directly benefit.
What this research studies
This project aims to create dynamic, data-driven tools that monitor kidney injury risk in the ICU after cardiac surgery. By analyzing electronic medical records with ensemble machine learning, the team hopes to provide real-time risk scores and recommendations. The goal is to help doctors tailor fluids, heart-support medications, and other interventions to reduce kidney damage and improve recovery. The work builds on preliminary findings showing accurate early warnings, with a plan to integrate CDS tools into clinical workflows.
Why it matters
Potential benefit: If successful, patients could experience fewer kidney complications and shorter, safer hospital stays after heart surgery.
How similar studies have gone: Previous small studies with ML have shown promise in predicting AKI; this project extends that work to dynamic, care-guiding predictions.
Where this research is happening
-
Baylor College of Medicine
Houston, United States Active
Researchers
- Principal investigator: Ghanta, Ravi K — Baylor College of Medicine
- Study coordinator: Ghanta, Ravi K
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.