Quantitative EEG-Based Seizure Estimation in Super-Refractory Status Epilepticus

Area of Science:

• Neuroscience
• Clinical Neurology
• Medical Technology

Background:

• Super-refractory status epilepticus (SRSE) presents diagnostic challenges.
• Accurate seizure burden quantification is crucial for SRSE management.
• Quantitative electroencephalography (qEEG) is a potential tool for seizure monitoring.

Purpose of the Study:

• To evaluate the accuracy of qEEG in determining seizure burden in SRSE patients.
• To compare qEEG performance between experienced and novice users.
• To assess the clinical utility of qEEG for SRSE seizure detection.

Main Methods:

• Retrospective review of EEG recordings from 69 SRSE patients (2009-2019).
• Seizure annotation by gold standard (raw EEG experts), qEEG experts, and qEEG novices.
• Comparison of seizure detection rates, false positive rates, and seizure burden estimates.

Main Results:

• qEEG experts demonstrated 93% sensitivity and 61% specificity, with good inter-rater agreement (κ=0.64).
• qEEG novices showed 98.5% sensitivity but only 13% specificity, with fair inter-rater agreement (κ=0.4).
• Seizure burden estimates by qEEG experts closely matched the gold standard, while novices overestimated it.

Conclusions:

• Both experienced and novice qEEG users achieved high sensitivity but low specificity for SRSE seizure detection.
• qEEG is a valuable tool for experienced users to estimate seizure burden in SRSE.
• Further refinement of qEEG analysis may improve specificity in SRSE monitoring.