Predicting kidney injury in critically ill children using advanced decision support tools
Pediatric Acute Kidney Injury Prediction Using Generalized, Sharable, Usable Decision Support
This study is working on a smart tool to help doctors spot when critically ill kids aged 0-11 might be at risk for kidney problems before they happen, so they can take action early and keep them safe.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Rochester NIH-funded |
| Lab location | 1 site (Rochester, United States) |
| Project ID | NIH-11003681 on NIH RePORTER |
What this research studies
This research focuses on improving the prediction of acute kidney injury (AKI) in critically ill children aged 0-11 years. By utilizing advanced machine learning techniques, the study aims to develop a decision support system that can identify patients at risk for AKI before it occurs, allowing for timely interventions. The approach addresses current limitations in existing prediction models and aims to create a more effective and user-friendly clinical decision support system. This could enhance patient safety and care quality in pediatric intensive care units.
Who could benefit from this research
Good fit: Ideal candidates for this research are critically ill children aged 0-11 years who are at risk for developing acute kidney injury.
Not a fit: Patients who are not critically ill or do not have risk factors for acute kidney injury may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to earlier identification and prevention of acute kidney injury in children, significantly improving their health outcomes.
How similar studies have performed: Previous research has shown promise in using machine learning for predicting health outcomes, indicating that this approach could be effective in pediatric settings as well.
Where this research is happening
Rochester, United States
- University of Rochester — Rochester, United States (Active)
Researchers
- Principal investigator: Dziorny, Adam C. — University of Rochester
- Study coordinator: Dziorny, Adam C.
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 below.