AI Article Synopsis

  • The study investigates how reducing antiseizure medication affects interictal epileptogenic discharges (IEDs) and seizure likelihood in epilepsy patients.
  • Findings indicate a significant spike in seizure activity when medication is minimized and an increase in spiking activity both before and after seizures.
  • This research highlights the potential for individualized monitoring of spike rates to better predict seizure risks for patients.

Article Abstract

Objective: To determine the influence of antiseizure medication (ASM) withdrawal on interictal epileptogenic discharges (IEDs) in scalp-EEG and seizure propensity.

Methods: We included 35 adult unifocal epilepsy patients admitted for presurgical evaluation in the EEG and Epilepsy Unit of Geneva between 2016 and 2020, monitored for at least 5 days. ASM was individually tapered down, and automated IED detection was performed using Epilog PreOp (Epilog NV, Belgium, Ghent). We compared spike rate per hour (SR) at day 1 when patients were on full medication (baseline) with SR at the day with the lowest dose of medication. To determine possible peri-ictal changes of SR, we compared SR 8 h before and after a seizure with the SR at the same time of the baseline day.

Results: Our results showed a significant increase in spiking activity in the day of lowest drug load if compared to spike rate at day on full medication (p < 0.001). The total amount of spikes during 24 h correlated significantly with seizure occurrence (p < 0.0001). We also revealed significant increase in peri-ictal SR, in particular 2-4 h preceding a seizure (p = 0.05) extending up to 3 h after the seizure (p = 0.03) with a short decrease just before seizure occurrence.

Conclusions: Our results suggest that SR increases with medication withdrawal and particularly before and after seizures. There is a complex pattern of increase and decrease around seizure onset which explains divergent results in previous studies.

Significance: Precise spike counting at similar circadian periods for a patient could help to determine the risk of seizure occurrence in a personalized fashion.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9615133PMC
http://dx.doi.org/10.1016/j.cnp.2022.09.004DOI Listing

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