Abstracts

Indications for Continuous EEG Monitoring: What Do They Tell Us?

Abstract number : 3.157
Submission category : 3. Neurophysiology / 3B. ICU EEG
Year : 2022
Submission ID : 2204534
Source : www.aesnet.org
Presentation date : 12/5/2022 12:00:00 PM
Published date : Nov 22, 2022, 05:25 AM

Authors :
Ahmad Mahadeen, MD – Cleveland Clinic Neurological Institute; Ifrah Zawar, MD – Department of Neurology – University of Virginia School of Medicine; Stephen Hantus, MD – Charles Shor Epilepsy Center – Cleveland Clinic Neurological Institute; Vineet Punia, MD – Charles Shor Epilepsy Center – Cleveland Clinic Neurological Institute

Rationale: While studies have explored clinical and electroencephalogram (EEG) characteristics as predictors of seizure occurrence on continuous EEG (cEEG), the role of primary indication for cEEG monitoring in predicting seizure occurrence has not been studied. The purpose of this study is to fill this knowledge gap.

Methods: After Institutional Review Board approval, we used our prospectively maintained cEEG database to identify all adults (≥18 years of age) who underwent cEEG monitoring at Cleveland Clinic during the 2016 calendar year. Patients with anoxic brain injury undergoing cEEG as part of hypothermia protocol were excluded. The remaining patients were divided into those who underwent cEEG for the primary indication of unexplained altered mental status (AMS) and those who had seizure like events (SLE; defined as motor events or patient reported events concerning for seizures to the primary treating team). Baseline characteristics including age, sex, monitoring duration, primary etiology, remote brain insult, neurological status, epilepsy history, use of anti-seizure medications (ASMs), interictal EEG findings were compared between the two indication groups. Categorical variables were described using frequencies and percentages, whereas continuous variables were described using medians and inter-quartile range (IQR; first‐third quartiles). Multivariable logistic regression was used to identify risk factors associated with seizure detection on cEEG (primary outcome).

Results: A total of 2227 patients (mean age 59.4 years) met the inclusion criteria. Among them, 882 (39.6%; 50% females) underwent cEEG for unexplained AMS and 1345 (60.4%; 51% females) for SLE. Patients who underwent cEEG for SLE were significantly younger compared to AMS patients (56.61 vs 63.76 years, p< 0.001). On the univariate analysis, patients with SLE were more likely to have epilepsy related breakthrough seizures (Odd’s ratio [OR]: 19.33, p < 0.001) and psychogenic non-epileptic events (OR: 5.71, p< 0.001) as the presumed etiology of presentation. They were more likely to have a history of epilepsy (OR: 2.78, p< 0.001), prior history of remote brain insults (OR: 1.41, p< 0.001) and were on ASMs (OR: 2.00, p< 0.001) at the time of cEEG initiation. They were more likely to have interictal epileptiform discharges (OR: 1.31, p=0.017) and less likely to have generalized periodic discharges (OR: 0.43, p < 0.001) on EEG. Three-hundred (13.5%) patients had seizures on cEEG of whom 16.7% (N=225) were in the SLE group compared to 8.5% (N=75) in the AMS group (OR: 2.16, p< 0.001). On multivariable logistic analysis, after accounting for all clinical and EEG factors, indication of SLE remained an independent predictor of seizure occurrence of EEG (OR: 2.60, CI: 1.77-3.88, p< 0.001).
Neurophysiology