A Longitudinal Imaging and Clinical Data Workflow Identifies Potential Time-Dependent Risk Factors for Post-Subarachnoid Hemorrhage Epilepsy.
Overview
- Department of Neurology and Rehabilitation, University of Illinois at Chicago,Chicago, IL USA
- Department of Biomedical Engineering, University of Illinois at Chicago,Chicago, IL USA
- Department of Mathematics, Statistics, and Computer Science, University of Illinois at Chicago,Chicago, IL USA
- Department of Neurology, University of Pennsylvania Perelman School of Medicine,Philadelphia, PA USA
Abstract
Objective: Subarachnoid hemorrhage (SAH) can lead to recurrent seizures, but the clinical factors that influence which patients will develop epilepsy remain unclear. We built a workflow integrating longitudinal clinical, laboratory, and brain imaging data to identify factors associated with post-SAH epilepsy.
Methods: Retrospective review of electronic medical records followed by direct patient contact was used to identify patients with nontraumatic SAH and determine whether they later developed epilepsy. A total of 58 longitudinal imaging, clinical, hematologic, coagulation, metabolic, and cerebrospinal fluid (CSF) variables were analyzed from the first 14 days following SAH. Blood location and ventricular size were quantified from serial computed tomography images using an automated pipeline. A two-step statistical approach was used to identify time-dependent variables associated with post-SAH epilepsy. Data-driven logistic regression modeling was implemented using features extracted from individual time series to identify which variables could be the most important for determining post-SAH epilepsy risk.
Results: Out of 134 patients, 15 (11.2%) developed post-SAH epilepsy. Patients who developed epilepsy had persistently lower Glasgow Coma Scores, increased total and pericortical blood volumes up to day 8, as well as elevated peripheral eosinophil counts and systemic immune-inflammatory index in the second week up to day 13 following SAH. Exploratory logistic regression analysis identified systemic immune-inflammatory index, total blood volume, and CSF white blood cells as the most influential variables.
Interpretation: We demonstrate the ability of a novel workflow combining longitudinal imaging and clinical data to identify potential risk factors for post-SAH epilepsy. While limited to a single-center retrospective cohort, we observed that pericortical blood in the first week and increased inflammation in the second week after SAH were associated with development of epilepsy. Our approach could be expanded to include more patients with SAH at multiple sites, inform future clinical trials to prevent post-SAH epilepsy, and explore other neurologic disorders.
Supplementary Information: The online version contains supplementary material available at 10.1007/
Reproduced under the paper's license (CC BY), from the paper cited above.
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Data
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package= , at cran.r-project.org; found in the referencespsfmi
Data Availability
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.
Reproduced under the paper's license (CC BY), from the paper cited above.
Versions
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Version 1, 30 September 2026: the first record
Recorded: type, language, journal, volume, issue, pages, dates, 13 authors, 4 keywords, 14 MeSH terms, 3 funders, 55 references.
Cite
This paper
Butler, M., Hao, Y., Wang, J., Maharathi, B., Serafini, A., Wong, J., Davis, J., Shah, P., Dachet, F., Geraghty, J. R., Testai, F. D., Pandey, D., & Loeb, J. A. (2026). A Longitudinal Imaging and Clinical Data Workflow Identifies Potential Time-Dependent Risk Factors for Post-Subarachnoid Hemorrhage Epilepsy. Neurocritical care, 45(1), 351-367. https://
BibTeX
@article{butler2026longi
author = {Butler, Mitchell and Hao, Yuncheng and Wang, Jing and Maharathi, Biswajit and Serafini, Anna and Wong, Jensen and Davis, Jared and Shah, Parin and Dachet, Fabien and Geraghty, Joseph R. and Testai, Fernando D. and Pandey, Dilip and Loeb, Jeffrey A.},
title = {{A Longitudinal Imaging and Clinical Data Workflow Identifies Potential Time-Dependent Risk Factors for Post-Subarachnoid Hemorrhage Epilepsy}},
journal = {Neurocritical care},
year = {2026},
month = mar,
volume = {45},
number = {1},
pages = {351--367},
publisher = {Springer Science+Business Media},
issn = {1541-6933},
doi = {10.1007/
url = {https://
pmid = {41857471},
pmcid = {PMC13369638}
}
RIS
TY - JOUR
AU - Butler, Mitchell
AU - Hao, Yuncheng
AU - Wang, Jing
AU - Maharathi, Biswajit
AU - Serafini, Anna
AU - Wong, Jensen
AU - Davis, Jared
AU - Shah, Parin
AU - Dachet, Fabien
AU - Geraghty, Joseph R.
AU - Testai, Fernando D.
AU - Pandey, Dilip
AU - Loeb, Jeffrey A.
TI - A Longitudinal Imaging and Clinical Data Workflow Identifies Potential Time-Dependent Risk Factors for Post-Subarachnoid Hemorrhage Epilepsy
T2 - Neurocritical care
J2 - Neurocrit Care
PY - 2026
DA - 2026/
VL - 45
IS - 1
SP - 351
EP - 367
SN - 1541-6933
PB - Springer Science+Business Media
DO - 10.1007/
UR - https://
LA - en
ER -
CSL-JSON
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