Improving predictions for outcomes in patients with acute brain injuries
Official title: Prospective Validation of Neurophysiologic Outcome Prediction in Acute Brain Injury
Funded at Beth Israel Deaconess Medical Center · NIH-11002008 · Data updated 2026-11-12
This study is looking to improve how doctors predict recovery for patients with serious brain injuries by using advanced technology to analyze brain wave patterns, helping to identify those at risk for seizures and long-term epilepsy, so they can provide better care.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Beth Israel Deaconess Medical Center NIH-funded |
| Lab location | 1 site (Boston, United States) |
| Project start | January 1, 2023 |
| Project end | December 31, 2027 |
| Funding year | 2025 |
| Award (this year) | $663,875 |
| NIH project number | 5R01NS126282-03 |
| Project ID | NIH-11002008 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals who have recently experienced an acute brain injury, such as traumatic brain injury or stroke.
✕Less likely to help
Patients with chronic neurological conditions unrelated to acute brain injuries may not benefit from this research.
What this research studies
This research focuses on enhancing the prediction of neurological outcomes for patients who have suffered acute brain injuries. By utilizing advanced machine learning algorithms, the study aims to analyze EEG data to identify patterns that could indicate the risk of seizures and long-term epilepsy. The research will involve collecting clinical and EEG data from 3,000 patients across multiple centers, allowing for a comprehensive validation of these predictive models. The ultimate goal is to translate these findings into practical tools that can be used in clinical settings to improve patient care.
Why it matters
Potential benefit: If successful, this research could lead to better management and treatment strategies for patients with acute brain injuries, potentially reducing the incidence of long-term disabilities.
How similar studies have gone: Previous research has shown promise in using machine learning approaches to analyze EEG data, indicating that this methodology could be effective in predicting outcomes in acute brain injury cases.
Where this research is happening
-
Beth Israel Deaconess Medical Center
Boston, United States Active
Researchers
- Principal investigator: Westover, Michael Brandon — Beth Israel Deaconess Medical Center
- Study coordinator: Westover, Michael Brandon
Related research
Other NIH-funded projects on the same topics.
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Sleep patterns predicting recovery after acute brain injury
Researchers will look at brain sleep signals to see if certain sleep patterns can forecast when patients who are unconscious after a brain injury may start to wake up and recover.
-
Brain cell ion balance and swelling after sudden brain injury
They are looking at how changes in ion levels and cell size after a sudden brain injury cause swelling or shrinkage for people with acquired brain injuries, including newborns.
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EEG tools to predict recovery after sudden brain injury
This project will use computer-based EEG tools to help doctors predict recovery and seizure risk for people hospitalized with sudden (acute) brain injuries.
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Using EEG to guide seizure medicines after stroke or head injury
This project looks at whether using bedside EEG brain monitoring to guide anti-seizure medicines for people with recent stroke or traumatic brain injury can prevent harmful brain activity while cutting down medicine side effects.
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Understanding Brain Injury During ECMO Treatment
This research looks at why some people develop brain injury when they receive life-saving ECMO support for severe heart and lung failure.
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Helping patients with acute brain injuries and their caregivers build resilience together
This study is for patients who have had a brain injury, like a stroke, and their caregivers, and it offers a friendly program called 'Recovering Together' to help them cope with stress and support each other while they heal in the hospital.
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.