Statistical methods to link high-dimensional heart-surgery data with outcomes
Official title: Statistical methods for quantifying the association between high-dimensional multi-channel hemodynamics data and cardiac surgery outcomes
Funded at Johns Hopkins University · NIH-11448221 · Data updated 2026-11-12
This grant tests advanced data methods to find links between detailed intraoperative heart-surgery measurements and patient outcomes after procedures like CABG.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Johns Hopkins University NIH-funded |
| Lab location | 1 site (Baltimore, United States) |
| Project start | September 1, 2026 |
| Project end | May 31, 2030 |
| Funding year | 2026 |
| Award (this year) | $778,985 |
| NIH project number | 1R01HL183064-01A1 |
| Project ID | NIH-11448221 on NIH RePORTER |
Who could benefit from this research
✓Could help
Patients undergoing cardiac surgeries such as CABG at participating centers who contribute data from their procedures and outcomes.
✕Less likely to help
Patients not undergoing cardiac surgery or those treated at non-participating centers may not benefit from these findings.
What this research studies
Researchers will combine continuous intraoperative hemodynamics data with post-surgery outcomes and electronic medical records from thousands of cardiac surgeries to build robust models. The project focuses on identifying modifiable factors during surgery that could improve results and reduce costs. The team has already assembled large, multi-source data sets from Johns Hopkins and collaborators to support rigorous analysis. Results could guide surgeons and teams in real-time decision-making and postoperative care. The work aims to translate complex statistics into practical insights for improving patient safety and value of care.
Why it matters
Potential benefit: If successful, this work could help personalize and improve cardiac surgery care, potentially reducing complications and costs.
How similar studies have gone: Large multi-center data analyses have shown promise in linking intraoperative factors to outcomes, but this project aims to advance methods for high-dimensional, multi-source data.
Where this research is happening
-
Johns Hopkins University
Baltimore, United States Active
Researchers
- Principal investigator: Crainiceanu, Ciprian M — Johns Hopkins University
- Study coordinator: Crainiceanu, Ciprian M
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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.