# Precise Prediction and Treatment of Seizures After Intracranial Hemorrhage

> **NIH NIH R01** · NORTHWESTERN UNIVERSITY · 2024 · $623,691

## Abstract

PROJECT SUMMARY
Seizures are a common and morbid complication of intracranial hemorrhage, leading to brain herniation, worse
patient outcome, and death. While a few risk factors for seizures have been described, the ability to predict
seizures is still crude. The inaccuracy of seizure prediction leads to imprecise administration of prophylactic
antiseizure medications. Prophylactic antiseizure medications are intended to prevent seizures, reduce
complications, and improve patient outcomes. Unfortunately, antiseizure medications have been independently
associated with more complications, worse patient outcomes, and worse health-related quality of life (HRQoL),
particularly cognitive function HRQoL. Better methods are needed to predict precisely which patients are likely
to have seizures after intracranial hemorrhage to prevent them, and, further, to determine which patients are
likely to benefit from prophylactic antiseizure medications.
We will continue a successful line of research. At the time we began to study this topic, prophylactic phenytoin
was recommended by guidelines. After publications implicated phenytoin with more complications and worse
patient outcomes, guidelines were changed to discourage the use of prophylactic phenytoin, and clinicians
broadly switched from phenytoin to levetiracetam. We recently reported that prophylactic levetiracetam is
independently associated with worse cognitive function HRQoL in the 40% of patients who receive it,
underscoring that current practice may lead to inadvertent harm, an untenable status quo. The effects of
seizures on HRQoL are worse than prophylactic antiseizure medication. Preventing seizures by precise
administration of prophylactic antiseizure medication would be helpful.
This proposal has two major aims that will improve patient outcomes after intracranial hemorrhage. First, we
will build upon our previous work to derive and validate a multi-dimensional model for predicting seizures after
intracranial hemorrhage from electroencephalography and imaging data to identify the patients most likely to
benefit from prophylactic seizure medication. A prospective database with recording of seizures and patient
outcomes provides preliminary data. Future data will be electronically abstracted from a health care system
with a single electronic health record using automated techniques from electroencephalography reports, raw
electroencephalography data, and neuroimaging source data. Then, we will determine the effect of
prophylactic seizure medication on patient HRQoL at high risk for seizures, and use other machine learning
techniques to determine which patients are most likely to benefit from prophylactic antiseizure medication. At
the conclusion of this proposal, we will deliver a model to predict patients most likely to have seizures, and
determine which patients are likely to have higher HRQoL as a results of prophylactic seizure medications,
leading to targeted treatment and non-treatment to max...

## Key facts

- **NIH application ID:** 10811744
- **Project number:** 5R01NS117608-02
- **Recipient organization:** NORTHWESTERN UNIVERSITY
- **Principal Investigator:** ANDREW M NAIDECH
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $623,691
- **Award type:** 5
- **Project period:** 2023-09-01 → 2029-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10811744

## Citation

> US National Institutes of Health, RePORTER application 10811744, Precise Prediction and Treatment of Seizures After Intracranial Hemorrhage (5R01NS117608-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10811744. Licensed CC0.

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