Event Characterization in Epilepsy Monitoring Units: Diagnostic Yield and Clinical Impact
Abstract number :
2.231
Submission category :
4. Clinical Epilepsy / 4B. Clinical Diagnosis
Year :
2024
Submission ID :
148
Source :
www.aesnet.org
Presentation date :
12/8/2024 12:00:00 AM
Published date :
Authors :
Anokhi Pawar, BS – Weill Cornell Medicine, Department of Neurology
Cenai Zhang, MS – Weill Cornell Medicine, Department of Neurology
Padmaja Kandula, MD – Weill Cornell Medicine, Department of Neurology, New York City,
Presenting Author: Hai Chen, MD, PhD – Weill Cornell Medicine, Department of Neurology
Rationale: Elective epilepsy monitoring unit (EMU) studies has been widely used in the diagnosis and treatment of epilepsy. We aim to investigate the yield of EMU in detecting and characterizing habitual events. Clinical impact of EMU was evaluated by monitoring anti-seizure medication (ASM) changes following the EMU.
Methods: We identified patients admitted in EMU to evaluate habitual events between Jan 1, 2023 and Sep 30, 2023. We extracted patient demographics, medical history, previous EEG and imaging findings, as well as the frequency and description of events that necessitated the monitoring. The findings were dichotomized into either a diagnostic-positive or a non-diagnostic study. A recording with findings of a habitual event (either a seizure or non-epileptic event) is considered a diagnostic-positive study.
Results: We identified 55 recordings during the time period and the event description included abnormal movements (n = 22), subjective sensation changes or speech changes (n = 15), altered awareness (n = 11) and syncope (n = 7). The event frequencies were daily (n = 12), weekly (n = 14), monthly (n = 18) or less than once a month (n = 11). The latency between initial event onset to EMU admission was less than 6 month (n = 18) or more than 6 month (n = 28). Table 1 summarizes patient demographic information and characteristics (Table 1). Diagnostic EMU studies accounted for 56% (31/55) of the recordings and the habitual events included epileptic seizure (n = 15) and psychogenic non-epileptic events (PNEE) (n=12) and physiological events (n = 4). Eight out of 15 (53%) patients who had a recorded seizure increased or initiated the ASM at discharge (Table 2). Reduction or elimination of ASM was found in 5 patients who had a non-epileptic event in the recording (n = 16) (Table 2).
Conclusions: Most patients had at least 6-month delay between onset of paroxysmal events and EMU evaluation. EMU study is valuable in evaluating paroxysmal events with a diagnostic yield of 56% in patients. A diagnostic-positive EMU study often leads to ASMs adjustments.
Funding: N/A
Clinical Epilepsy