AI-guided care for sudden hydrocephalus
Official title: Machine Learning to Optimize Management of Acute Hydrocephalus
Funded at Columbia University Health Sciences · NIH-11370118 · Data updated 2026-11-12
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 start | May 15, 2023 |
| Project end | April 30, 2028 |
| Funding year | 2026 |
| Award (this year) | $630,988 |
| NIH project number | 5R01NS131606-04 |
| Project ID | NIH-11370118 on NIH RePORTER |
Who could benefit from this research
✓Could help
People with acute hydrocephalus after intracerebral hemorrhage (ICH) or subarachnoid hemorrhage (SAH) who have an external ventricular drain in place are the primary candidates.
✕Less likely to help
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.
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.
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 gone: 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
-
Columbia University Health Sciences
New York, United States Active
Researchers
- Principal investigator: Park, Soojin — Columbia University Health Sciences
- Study coordinator: Park, Soojin
Related research
Other NIH-funded projects on the same topics.
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Targeting the brain’s fluid system to treat post-hemorrhagic hydrocephalus
This grant explores a new approach to treating post-hemorrhagic hydrocephalus by studying how the brain’s fluid system and immune cells manage CSF after a brain bleed.
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Endoscopic versus Shunt Treatment of Hydrocephalus in Infants
A study compares two treatments for hydrocephalus in infants to see which keeps babies cognitively on par with the standard shunt treatment.
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Endoscopic treatment versus shunt for hydrocephalus in infants
This project tests whether a shunt-free endoscopic procedure can be as good as traditional shunting for babies with hydrocephalus.
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Endoscopic treatment vs shunt for infant hydrocephalus
Infants with hydrocephalus may be treated with a shunt or a shunt-free procedure called ETV+CPC, and this study compares the two to see if the shunt-free option can keep cognitive outcomes similar.
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Functional screen of hydrocephalus and heart-disease genes in a frog model
A study uses frog embryos to test how human genetic changes might cause congenital hydrocephalus and related heart defects, with the goal of understanding why these conditions occur.
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Modulating choroid plexus function to restore CSF balance in hydrocephalus
A new NIH grant aims to adjust the choroid plexus, the brain’s CSF factory, to restore normal CSF flow and reduce hydrocephalus-related problems.
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.