Interictal epileptiform activity as an independent predictor of electrographic seizures in critically ill patients undergoing continuous electroencephalographic monitoring

Abstract

Background: Electrographic seizures frequently occur in critically ill patients and often remain clinically unrecognized. Continuous electroencephalographic monitoring has therefore become an essential tool for seizure detection in intensive care settings. Identifying electroencephalographic predictors of seizure occurrence may improve risk stratification and help prioritize patients who would benefit most from prolonged monitoring. Objective: To identify clinical and electroencephalographic predictors of electrographic seizure detection in critically ill patients undergoing continuous electroencephalographic monitoring. Methods: Prospective cohort study including 173 critically ill patients undergoing continuous electroencephalographic monitoring for indications such as altered level of consciousness, suspected seizures, abnormal movements, or evaluation of encephalopathy. Electroencephalographic recordings were obtained using the international 10–20 system and reviewed by experienced neurophysiologists. Variables analyzed included age, sex, presence of severe encephalopathy, and interictal epileptiform activity. Logistic regression models were constructed to evaluate predictors of electrographic seizure occurrence. Results: Electrographic seizures occurred in 35 patients (20.2%). Interictal epileptiform abnormalities were present in 84 patients (48.6%). In univariate analysis, epileptiform activity was strongly associated with seizure detection (odds ratio 3.24; 95% confidence interval 1.58–6.63; p=0.001). In multivariate logistic regression analysis adjusting for age, sex, and encephalopathy severity, interictal epileptiform activity remained the only independent predictor of electrographic seizure detection (adjusted odds ratio 3.08; 95% confidence interval 1.47–6.45; p=0.003). Age, sex, and severe encephalopathy were not independently associated with seizure occurrence. Conclusion: Interictal epileptiform activity increased the likelihood of electrographic seizure detection by approximately threefold. These findings suggest that epileptiform abnormalities represent an important electrophysiological biomarker of cortical hyperexcitability and may help identify critically ill patients at higher risk for seizures during continuous electroencephalographic monitoring.