Patterns of Recording Epileptic Spasms in an Electronic Seizure Diary Compared With Video-EEG and Historical Cohorts.

BACKGROUND: Use of electronic seizure diaries (e-diaries) by caregivers of children with epileptic spasms is not well understood. We describe the demographic and seizure-related information of children with epileptic spasms captured in a widely used e-diary and explore the potential biases in how caregivers report these data. METHODS: We analyzed children with epileptic spasms in an e-diary, Seizure Tracker, from 2007 to 2018. We described variables including sex, time of seizure, percentage of spasms occurring as individual spasms (versus in clusters), cluster duration, and number of spasms per cluster. We compared seizure characteristics in the e-diary cohort with published cohorts to identify biases in caregiver-reported epileptic spasms. We also reviewed seizure patterns in a small cohort of children with epileptic spasms monitored on overnight video-electroencephalography (vEEG). RESULTS: There were 314 children in the e-diary cohort and nine children in the vEEG cohort. The e-diary cohort was more likely than expected to report counts divisible by five. The e-diary cohort had a lower proportion of nighttime spasms than expected based on data from published cohorts. The e-diary cohort had a significantly lower percentage of spasms as individual spasms, a greater number of spasms per cluster, and a greater cluster duration relative to the vEEG cohort. CONCLUSIONS: Caregivers using e-diaries for epileptic spasms may miss individual spams, be more likely to report long clusters, round counts to the nearest five, and underreport nighttime spasms. Clinicians should be aware of these reporting biases when using e-diary data to guide care for children with epileptic spasms.

Daylight saving time transitions are not associated with increased seizure incidence.

OBJECTIVE: Given the known association of daylight saving time (DST) transitions with increased risk of accidents, heart attack, and stroke, we aimed to determine whether seizures, which are reportedly influenced by sleep and circadian disruption, also increased in frequency following the transition into DST. METHODS: Using Seizure Tracker's self-reported data from 12 401 individuals from 2008-2016, 932 717 seizures were assessed for changes in incidence in relation to DST transitions. Two methods of standardization-z scores and unit-scaled rate ratios (RRs)-were used to compare seizure propensities following DST transitions to other time periods. RESULTS: As a percentile relative to all other weeks in a given year, absolute seizure counts in the week of DST fell below the median (DST seizure percentiles mean ± SD: 19.68 ± 16.25, P = 0.01), which was concordant with weekday-specific comparisons. Comparatively, RRs for whole-week (1.06, 95% confidence interval [CI] 1.02-1.10, P = 0.0054) and weekday-to-weekday (RR range 1.04-1.16, all P < 0.001) comparisons suggested a slightly higher incidence of seizures in the DST week compared to all other weeks of the year. However, examining the similar risk of the week preceding and following the DST-transition week revealed no significant weekday-to-weekday differences in seizure incidence, although there was an unexpected, modestly decreased seizure propensity in the DST week relative to the whole week prior (RR 0.94, 95% CI 0.91-0.96, P < 0.001). SIGNIFICANCE: Despite expectations that circadian and sleep disruption related to DST transitions would increase the incidence of seizures, we found little substantive evidence for such an association in this large, longitudinal cohort. Although large-scale observational/epidemiologic cohorts can be effective at answering such questions, additional covariates (eg, sleep duration, seizure type, and so on) that may underpin the association were not able available, so the association has not definitively been ruled out.

Circadian and circaseptan rhythms in human epilepsy: a retrospective cohort study.

BACKGROUND: Epilepsy has long been suspected to be 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 environmental factors. This study aimed to quantify the strength and prevalence of seizure cycles at multiple temporal scales across a large cohort of people with epilepsy. METHODS: This retrospective cohort study used the two most comprehensive databases of human seizures (SeizureTracker [USA] and NeuroVista [Melbourne, VIC, Australia]) and analytic techniques from circular statistics to analyse patients with epilepsy for the presence and frequency of multitemporal cycles of seizure activity. NeuroVista patients were selected on the basis of having intractable focal epilepsy; data from patients with at least 30 clinical seizures were used. SeizureTracker participants are self selected and data do not adhere to any specific criteria; we used patients with a minimum of 100 seizures. The presence of seizure cycles over multiple time scales was measured using the mean resultant length (R value). The Rayleigh test and Hodges-Ajne test were used to test for circular uniformity. Monte-Carlo simulations were used to confirm the results of the Rayleigh test for seizure phase. FINDINGS: We used data from 12 people from the NeuroVista study (data recorded from June 10, 2010, to Aug 22, 2012) and 1118 patients from the SeizureTracker database (data recorded from Jan 1, 2007, to Oct 19, 2015). At least 891 (80%) of 1118 patients in the SeizureTracker cohort and 11 (92%) of 12 patients in the NeuroVista cohort showed circadian (24 h) modulation of their seizure rates. In the NeuroVista cohort, patient 8 had a significant cycle at precisely 1 week. Two others (patients 1 and 7) also had approximately 1-week cycles. Patients 1 and 4 had 2-week cycles. In the SeizureTracker cohort, between 77 (7%) and 233 (21%) of the 1118 patients showed strong circaseptan (weekly) rhythms, with a clear 7-day period. Between 151 (14%) and 247 (22%) patients had significant seizure cycles that were longer than 3 weeks. Seizure cycles were equally prevalent in men and women, and peak seizure rates were evenly distributed across all days of the week. INTERPRETATION: Our results suggest that seizure cycles are robust, patient specific, and more widespread than previously understood. They align with the accepted consensus that most epilepsies have some diurnal influence. Variations in seizure rate have important clinical implications. Detection and tracking of seizure cycles on a patient-specific basis should be standard in epilepsy management practices. FUNDING: Australian National Health and Medical Research Council.