Abstract Details

Title Prognostic Value of EEG Background, Reactivity, and Sleep Features in Pediatric OHCA

Topic Epilepsy/Clinical Neurophysiology (EEG)

Presentation(s) P8 - Poster Session 8 (11:45 AM-12:45 PM)

Poster/Presentation
Number 10-003

Objective To evaluate the prognostic utility of early electroencephalographic (EEG) findings in pediatric out-of-hospital cardiac arrest (OHCA) patients, examining the associations between EEG background, sleep features and reactivity with key clinical outcomes including mortality, early death within 48 hours and severe neurological impairment (defined as PCPC change ≥2) and using that as a prognostication tool

Background Electroencephalography (EEG) is widely used in post–cardiac arrest care, but its prognostic utility in pediatric out-of-hospital cardiac arrest (OHCA) remains incompletely defined

Design/Methods We analyzed EEG data from 218 pediatric OHCA patients (mean age 5.4 years, range 0.01–18 years). EEG features included background (normal, discontinuous, burst suppression, attenuated/suppressed), the presence of sleep features, reactivity and seizures. Outcomes were mortality, death within 48 hours of admission, and severe neurological decline (change in PCPC ≥2). Associations were assessed using Chi-square/Fisher’s exact tests with false discovery rate correction

Results Abnormal EEG background strongly predicted adverse outcomes. Burst suppression or flat patterns were associated with significantly higher overall mortality (p<0.0001), early death (p<0.0001) and severe neurological impairment (p<0.0001), while normal or discontinuous backgrounds correlated with improved survival and neurological outcomes (specificity >0.90 in several models). The presence of sleep features and EEG reactivity were overall protective showing significantly lower rates of mortality, death within 48 hours and severe outcome when present (all p≤0.002). Seizure occurrence was not associated with any outcome (p>0.29)

Conclusions EEG background, reactivity and sleep features provide strong prognostic information following pediatric OHCA, whereas seizures lack predictive value. Early incorporation of these EEG biomarkers into clinical assessment may improve risk stratification and guide management decisions in this high-risk population

Authors/Disclosures
Janine E. Taitt, MBBS (Medical College of Wisconsin and Affiliated Hospitals) PRESENTER	Dr. Taitt has nothing to disclose.
Binod Balakrishnan (Medical College of Wisconsin)	No disclosure on file
Mikal Shankey, DO	Dr. Shankey has nothing to disclose.
Maya Giaquinta, MD	Dr. Giaquinta has nothing to disclose.
Raquel Farias-Moeller, MD (Medical College of Wisconsin)	Dr. Farias-Moeller has nothing to disclose.

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