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. 2024 Aug;271(8):5137-5145.
doi: 10.1007/s00415-024-12464-4. Epub 2024 May 31.

Predictors of seizure detection and EEG clinical impact in an italian tertiary emergency department

Anna Bellini  1   2 , Davide Gusmeo Curti  1   2   3 , Marco Cursi  2 , Giordano Cecchetti  1   2   4 , Federica Agosta  1   4   3 , Giovanna F Fanelli  1   2 , Massimo Filippi  5   6   7   8   9
Affiliations

Predictors of seizure detection and EEG clinical impact in an italian tertiary emergency department

Anna Bellini et al. J Neurol. 2024 Aug.

Abstract

Background and objectives: Epileptic seizures pose challenges in emergency departments (ED), affecting up to 10% of admitted patients. This study aimed to assess emergency electroencephalogram (EmEEG) utilization, identifying factors predicting seizure detection and its influence on clinical decisions.

Methods: A retrospective review of 1135 EmEEGs on 1017 patients at a tertiary teaching hospital between June 2022 and June 2023 was conducted. Data included demographics, medical history, EmEEG indications, neuroimaging findings, and clinical outcomes. Statistical analyses utilized Fisher's exact tests and logistic regression models.

Results: EmEEG detected status epilepticus-related seizures in 5.40% of cases, seizures without status epilepticus in 3.05%, and status epilepticus without discrete seizures in 3.74%. Epileptiform abnormalities were noted in 22.12% of EmEEGs. EmEEG influenced initial diagnoses (21.24%), antiseizure medication changes (20.85%), and discharge decisions (39.04%). Predictors for seizures/status epilepticus included previous neurosurgery, seizures in the ED, and cognitive/behavioral impairment (p < 0.001). EmEEG significantly altered initial diagnoses based on witnessed seizures, involuntary movements, epileptiform abnormalities, and 1-2 Hz generalized periodic discharges (p < 0.001). Changes in antiseizure medications correlated with seizure occurrence, neuroimaging results, epileptiform abnormalities, and EEG background slowing (p < 0.001). Factors influencing discharge decisions included previous neurosurgery, consciousness impairment, acute neuroimaging pathology, EEG focal slowing, and EEG background slowing (p < 0.001).

Discussion: The study clarifies EmEEG's role in modifying initial diagnoses, treatment approaches, and discharge decisions. The study provides insights into the nuanced impact of EmEEG in different clinical scenarios, offering valuable guidance for clinicians in selecting patients for EmEEG, particularly in conditions of limited EEG availability.

Keywords: EEG clinical usefulness; Emergency EEG; Emergency department; Patients management; Seizures detection.

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