Creating a system to predict respiratory failure after surgery
Official title: Development of a predictive model and electronic health record-based probability scoring system and dashboard for postoperative respiratory failure
Funded at University of California at Davis · NIH-10895271 · Data updated 2026-11-12
This study is looking at what might cause breathing problems after surgery in adults, so doctors can better predict who might be at risk and help keep patients safe and healthy during their recovery.
Quick facts
| Grant type | Career grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California at Davis NIH-funded |
| Lab location | 1 site (Davis, United States) |
| Project start | August 1, 2023 |
| Project end | July 31, 2028 |
| Funding year | 2024 |
| Award (this year) | $183,384 |
| NIH project number | 5K01HL168222-02 |
| Project ID | NIH-10895271 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are adults aged 21 and older who are scheduled for elective surgical procedures.
✕Less likely to help
Patients who are not undergoing elective surgeries or those with pre-existing severe respiratory conditions may not benefit from this research.
What this research studies
This research aims to identify factors that contribute to different types of postoperative respiratory failure in adults who have undergone elective surgery. By analyzing data from electronic health records, the team will develop a predictive model and a scoring system that can help healthcare providers assess the risk of respiratory failure in patients. The goal is to improve patient outcomes by preventing this serious complication through better risk assessment and management strategies. Patients will be monitored for various pre- and intra-operative factors that may influence their recovery.
Why it matters
Potential benefit: If successful, this research could significantly reduce the incidence of postoperative respiratory failure, leading to better recovery outcomes and lower healthcare costs for patients.
How similar studies have gone: Previous research has shown promise in using predictive models for postoperative complications, indicating that this approach could be effective.
Where this research is happening
-
University of California at Davis
Davis, United States Active
Researchers
- Principal investigator: Stocking, Jacqueline C — University of California at Davis
- Study coordinator: Stocking, Jacqueline C
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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.