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A Longitudinal Imaging and Clinical Data Workflow Identifies Potential Time-Dependent Risk Factors for

Mitchell Butler1,2, Yuncheng Hao3, Jing Wang3

  • 1Department of Neurology and Rehabilitation, University of Illinois at Chicago, Chicago, IL, USA.

Neurocritical Care
|March 20, 2026
PubMed
Summary

Subarachnoid hemorrhage (SAH) can cause epilepsy. Increased blood in the brain and inflammation in the weeks following SAH are key risk factors for developing epilepsy after this condition.

Keywords:
Data scienceEpilepsySeizuresSubarachnoid hemorrhage

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Area of Science:

  • Neurology
  • Neurosurgery
  • Neuroscience

Background:

  • Subarachnoid hemorrhage (SAH) is a critical neurological condition often leading to secondary seizures.
  • Identifying patients at high risk for developing post-SAH epilepsy is crucial for timely intervention.
  • Current understanding of clinical factors predicting post-SAH epilepsy is limited.

Purpose of the Study:

  • To develop and validate a workflow integrating longitudinal clinical, laboratory, and neuroimaging data.
  • To identify key factors associated with the development of epilepsy following nontraumatic SAH.
  • To establish a predictive model for post-SAH epilepsy risk.

Main Methods:

  • Retrospective analysis of electronic medical records and patient follow-up.
  • Analysis of 58 longitudinal variables including imaging, clinical, hematologic, and CSF parameters within 14 days of SAH.
  • Utilized an automated pipeline for quantifying blood volume and ventricular size from CT scans.
  • Employed a two-step statistical approach with logistic regression for time-dependent variable analysis.

Main Results:

  • 11.2% of patients (15/134) developed post-SAH epilepsy.
  • Epilepsy patients exhibited lower Glasgow Coma Scores and increased total/pericortical blood volumes up to day 8.
  • Elevated peripheral eosinophil counts and systemic immune-inflammatory index were observed in the second week post-SAH.
  • Logistic regression identified systemic immune-inflammatory index, total blood volume, and CSF white blood cells as most influential predictors.

Conclusions:

  • A novel workflow combining longitudinal data effectively identifies potential risk factors for post-SAH epilepsy.
  • Pericortical blood (first week) and inflammation (second week) post-SAH are associated with epilepsy development.
  • The approach can be expanded for multi-center studies and inform future preventative clinical trials for post-SAH epilepsy.