Do changes in antiseizure medication affect seizure timing?
Reynolds, A.; Stirling, R. E.; Hakansson, S.; Karoly, P.; Lai, A.; Grayden, D. B.; Cook, M. J.; Nurse, E. S.; Peterson, A.
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Key points1. Antiseizure medications may change how strongly seizures synchronise with seizure cycles estimated from seizure diaries. 2. One seizure rate can be produced by different seizure cycles, suggesting a one-to-many relationship between seizure rate and cycles. 3. Using seizure cycles to time medication and assess efficacy could prove challenging with paper-based monitoring due to the complexity of cycles and potential drug effects. A seizure cycle tracking algorithm combined with an electronic seizure diary might support this task. Evaluating effectiveness of anti-seizure medications in epilepsy often relies on seizure frequency, reported through seizure diaries before and after treatment initiation. Measuring efficacy with seizure frequency can be challenging and unreliable as seizures tend to occur in cyclical patterns-- seizure cycles--making it difficult to distinguish drug effects from natural fluctuations. Incorporating cycle information could aid treatment evaluation, but antiseizure medications (ASMs) may alter seizure cycles, warranting further study. We conducted an observational study using seizure and ASM tracking app data (Feb. 2023) from 86 individuals with epilepsy. Participants were grouped based on ASM regimen and [≥]50% seizure rate reduction at 4 months after a drug change (drug-switching-responders, n=7/45; drug-switching-non-responders, n=38/45) or random timepoint (drug-sustained-responders, n=8/41; drug-sustained-non-responders, n=33/41). We compared groups on three seizure cycle variables detected via diaries: 1. how strongly seizures synchronise with a cycle, measured by the Synchronisation Index (SI), 2. cycle period, and 3. number of detected cycles. Permutation tests (=0.05, p<0.004 with Bonferroni correction) assessed significance, and regression models examined correlations with seizure rate. Across an average 612-day study period, 22,976 seizures were reported. Following an ASM change, the SI of the seizure cycle was more likely to change (p<0.004). This was pronounced in drug-switching-responders (median absolute SI difference: 0.37 [IQR=0.26] vs. 0.11 [IQR=0.11] in the drug-sustained-responders, p<0.004, permutation test). Changes in cycle length and number of detected cycles were similar across groups, possibly due to a non-linear relationship between seizure rate and cycles, suggested by weak linear correlations and poorly fitting models. These findings suggest ASMs may influence how strongly seizures synchronise with diary-detected seizure cycles. However, this relationship is complex and not yet well understood, complicating clinical interpretation. Ongoing research into real-time seizure cycle tracking may support the use of seizure cycles in aiding treatment monitoring.
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