Predicting kidney disease worsening in adults with sickle cell anemia
Predicting Progression of Chronic Kidney Disease in Sickle Cell Anemia Using Machine Learning Models (PREMIER)
Using computer learning to spot which adults with sickle cell anemia are most likely to have their kidney disease get worse.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Tennessee Health Sci Ctr NIH-funded |
| Lab location | 1 site (Memphis, United States) |
| Project ID | NIH-11161553 on NIH RePORTER |
What this research studies
If you join, researchers will use your medical records, blood and urine tests, and genetic results to train computer models that try to predict who will have faster kidney decline. The team looks at measurements such as albumin in the urine, eGFR trends, hemoglobin levels, APOL1 genetic variants, and medications like ACE inhibitors, ARBs, or hydroxyurea. Models will be developed and tested to flag patients at high risk of rapid kidney function loss. The goal is to identify people who may need closer monitoring or targeted care to slow progression.
Who could benefit from this research
Good fit: Adults (21+) with sickle cell anemia, especially individuals of African descent who have albuminuria or declining kidney function, are the ideal participants.
Not a fit: People without sickle cell disease, children under 21, or those without available clinical or genetic data are unlikely to be eligible or to benefit directly.
Why it matters
Potential benefit: Could help doctors identify high-risk patients earlier so they can receive closer monitoring or treatments that might slow kidney damage.
How similar studies have performed: Short-term studies show ACE inhibitors, ARBs, and hydroxyurea can reduce albuminuria and prior machine-learning work has shown promise in flagging high-risk patients, but long-term prevention of kidney decline in sickle cell disease remains unproven.
Where this research is happening
Memphis, United States
- University of Tennessee Health Sci Ctr — Memphis, United States (Active)
Researchers
- Principal investigator: Ataga, Kenneth I — University of Tennessee Health Sci Ctr
- Study coordinator: Ataga, Kenneth I
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.