AI-guided care for sudden hydrocephalus
Machine Learning to Optimize Management of Acute Hydrocephalus
This project uses artificial intelligence to help doctors decide when to sample spinal fluid, remove temporary drains, and who may need a permanent shunt after sudden hydrocephalus from brain bleeding.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Columbia University Health Sciences NIH-funded |
| Lab location | 1 site (New York, United States) |
| Project ID | NIH-11370118 on NIH RePORTER |
What this research studies
After brain bleeding some people need a temporary drain (an external ventricular drain, or EVD) but clinicians vary in how and when they check the drain or remove it. The team will train computer algorithms on clinical data and device measurements to spot early signs of EVD-related infection and predict who will later need a permanent cerebrospinal fluid (CSF) shunt. They will use past patient records and monitoring data to build the models and then test the tools in hospital care to try to shorten drain duration and reduce unnecessary fluid sampling. The aim is to help clinicians make safer, earlier decisions so patients spend less time on drains and in the hospital.
Who could benefit from this research
Good fit: People with acute hydrocephalus after intracerebral hemorrhage (ICH) or subarachnoid hemorrhage (SAH) who have an external ventricular drain in place are the primary candidates.
Not a fit: People without an EVD, those with non-acute or non-hemorrhagic hydrocephalus, or those already living with a permanent shunt are unlikely to benefit directly.
Why it matters
Potential benefit: If successful, this could lower EVD-related infections, shorten time with drains and hospital stays, and reduce unnecessary permanent shunt placements.
How similar studies have performed: Related AI approaches for ICU monitoring and infection prediction have shown promise, but applying machine learning specifically to EVD management is relatively new.
Where this research is happening
New York, United States
- Columbia University Health Sciences — New York, United States (Active)
Researchers
- Principal investigator: Park, Soojin — Columbia University Health Sciences
- Study coordinator: Park, Soojin
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.