Predicting Seizure Risk from Routine Electroencephalographs in Medical Intensive Care Units Using the 2HELPS2B Score

Area of Science:

• Neurology
• Clinical Neurophysiology

Background:

• Seizures are a common concern in medical intensive care units (MICUs).
• Predicting seizures from routine electroencephalographs (rEEGs) is crucial for timely intervention.

Purpose of the Study:

• To evaluate the 2HELPS2B score's utility in predicting seizures based on rEEG findings.
• To determine the optimal 2HELPS2B score cutoff for seizure prediction and guiding antiseizure medication (ASM) treatment.

Main Methods:

• Analysis of 670 rEEGs from MICU patients between October 2018 and March 2023.
• Evaluation of seizure occurrence in relation to rEEG characteristics and the 2HELPS2B score.
• Correlation of seizure incidence with factors like a history of seizures and altered consciousness.

Main Results:

• Seizures were frequent in patients with specific rEEG patterns and a history of seizures.
• The seizure rate increased significantly with higher 2HELPS2B scores (12% for score 1 to 100% for score ≥ 4).
• A 2HELPS2B score ≥ 2 was identified as the optimal cutoff for predicting post-rEEG seizures and guiding ASM treatment.

Conclusions:

• The 2HELPS2B score is a valuable tool for predicting seizures using rEEG data.
• This score can aid clinicians in identifying patients who may benefit from antiseizure medication (ASM).
• The findings support the use of the 2HELPS2B score in managing patients at risk for seizures in the MICU setting.