Subclinical seizure burden and cognitive impairment: The value of ambulatory EEG monitoring in underserved populations.
TL;DR
Evaluated seizure-detection rate with aEEG in an underserved epilepsy population and how it relates to self-reported seizure control is examined to highlight the importance of objective monitoring beyond patient self-report, particularly in vulnerable populations.
Abstract
Objectives
Ambulatory electroencephalography (aEEG) allows prolonged outpatient monitoring and improves seizure detection compared with routine EEG, particularly for subclinical seizures. aEEG is especially valuable in underserved populations, where socioeconomic barriers and comorbidities contribute to delayed diagnosis and poor seizure control. The objective of the study is to evaluate seizure-detection rate with aEEG in an underserved epilepsy population and to examine how it relates to self-reported seizure control. Clinical and socioeconomic factors influencing the discrepancy between actual vs perceived seizure control were examined.
Methods
This is a retrospective, cross-sectional study of adult patients who underwent aEEG at the University of Illinois Hospital, Chicago, Illinois. Demographic and clinical data (seizure history, medications, aEEG findings, and presence of psychiatric and cognitive comorbidities) were extracted from electronic medical records. Participants were grouped according to the presence or absence of seizures on aEEG. Univariate analyses and multivariate logistic regression were used to identify predictors of seizures detected on aEEG, whereas secondary analyses examined discrepancies between reported seizure frequency and the presence of seizure on aEEG.
Results
Of 382 patients included, seizures were captured on aEEG in 46 patients (12%), the majority of which were subclinical (80%). Patients with seizures on aEEG were more likely to be unemployed or on disability, have focal epilepsy, be prescribed a greater number of anti-seizure medications (ASMs), and have mild cognitive impairment (MCI). In multivariate analysis, number of ASMs (odds ratio [OR] 2.10, 95% confidence interval [CI] 1.44-3.07) and presence of MCI (OR 6.13, 95% CI 3.04-12.38) independently predicted seizures on aEEG. MCI was present in ~70% of patients with subclinical seizures who were reporting rare seizures at home.
Significance
aEEG detects subclinical seizures that often go unrecognized by patients. The presence of seizures has been shown to be associated with MCI. This highlights the importance of objective monitoring beyond patient self-report, particularly in vulnerable populations.