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June 1, 2026Critical Care Medicine

Point-of-Care Artificial Intelligence Measure of Seizure Burden Associates With Clinical Outcome at Discharge

Josef Parvizi M Salas Mariel Kalkach Aparicio Sahar F. Zafar Masoom Desai Suganya Karunakaran A. K. Gupta Baharan Kamousi Lawrence J. Hirsch Aaron F. Struck

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Key Points

This analysis aims to evaluate the relationship between AI-measured seizure burden and clinical outcomes at discharge.
Conducted secondary cohort analysis of the SAFER-EEG study.
Analyzed EEG and clinical data from 400 patients across three academic centers.
Evaluated peak seizure burden using bedside and online AI algorithms.
39.8% of patients had a peak seizure burden greater than 0% based on the bedside algorithm.
Each additional hour of detected seizure corresponded to increased odds of unfavorable outcome (aOR, 1.98; 95% CI, 1.11-4.29).
Combining outputs from both AI algorithms resulted in stronger outcome associations, particularly in patients with peak seizure burden ≥ 90% (aOR, 4.4; 95% CI, 1.66-12.69).

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Implication

Cohort analysis shows AI-measured seizure burden relates to clinical outcomes in patients, indicating potential benefits.

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Cite This Study

Parvizi et al. (2026) studied this question.

synapsesocial.com/papers/6a1fc530dee9eb8c0dce6a30 https://doi.org/10.1097/ccm.0000000000007158

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