Abstracts

Rationale: It has long been suspected that epilepsy is governed by cyclic rhythms, with seizure rates rising and falling periodically over weeks, months, or even years. The very long scales of seizure patterns seem to defy natural explanation and have sometimes been attributed to hormonal cycles, or other environmental factors.There are few large scale, patient-specific studies investigating multi-day seizure cycles. Most insight into slow seizure cycles (months to years) is based on research from centuries ago. Modern research has tended to ignore patient-specific patterns, has been limited to short-term recordings or smaller patient cohorts, or has monitored interictal activity rather than clinical seizures. Methods: This study used the two most comprehensive databases of human seizures, SeizureTracker.com and NeuroVista, to investigate multi-day cycles over long recording periods. The SeizureTracker.com data contains over 12,000 seizures self-reported by over 1000 patients. The NeuroVista data consists of over 3,000 seizures from continuously recorded electrocorticography in 15 patients. These two databases are highly complementary. SeizureTracker.com provides events from a large cohort, whereas NeuroVista provides seizure timing from fewer people but with high accuracy. We measured cycles at multiple temporal scales (from 6 hours to 3 months) by calculating the mean resultant length (R-value)for the phase of individual’s seizure times. High R-values indicate a high degree of phase-locking to a particular cycle (see Fig. 1). Results: Our results convincingly demonstrate that multi-day cycles are significant and highly prevalent, with findings consistent for both datasets. Fig. 2 shows that 80% of patients showed circadian (24-hour) modulation of their seizure rates. This aligns with the accepted consensus that most epilepsies have some diurnal influence. Of greater interest, 8% of patients showed strong circaseptan (weekly) rhythms, with a clear 7-day period. Furthermore, 19% of patients also had significant seizure cycles that were longer than three weeks. Seizure cycles were equally prevalent in males and females, and peak seizure rates were evenly distributed across all days of the week. Conclusions: The causes of multiscale variation in seizure rates are likely to include a range of environmental and endogenous factors. However, our results suggest that seizure cycles are robust, patient-specific, and more widespread than previously thought. Multiscale oscillations in seizure rates should be immediately recognized in clinical practice. The implications of ignoring these cycles are profound. For instance, treatment decisions may differ depending on which point in a patient’s cycle that assessment occurs. Detecting and tracking seizure cycles on a patient-specific basis should be part of standard epilepsy management practice. Funding: The research was funded by an Australian National Health and Medical Research Council Project Grant (APP1065638).