Seizure cycles in paediatric epilepsy

Author:

Kamitakahara HannahORCID,Karoly Philippa J.ORCID,Stirling Rachel E.,Eden Dominique,Nurse Ewan S.ORCID,Dabscheck Gabriel,Freestone Dean,Cook Mark J.,D’Souza Wendyl,Naim-Feil JodieORCID

Abstract

AbstractMultiday cyclic patterns underlying the timing of seizures are well-established in adults with epilepsy and are critical to the development of seizure risk forecasting models. As cycles underpinning these models are yet to be explored in paediatric cohorts, the current study applies methods drawn from seizure risk forecasting to identify and compare multiday seizure cycles between paediatric and adult cohorts. This is followed by the first validation of personalised forecasts of seizure likelihood in a paediatric cohort. Multiday seizure cycles were extracted retrospectively from 325 (71 paediatric) electronic seizure diary users (more than 28 days of app use) with confirmed epilepsy. Cycles were grouped (k-means clustering), and seizure cycles quantified (synchronisation index), with significant cycles identified by Rayleigh test of periodicity (p<0.05). Wilcoxon rank-sum test assessed differences in prevalence and strength of cycle groups between paediatric and adult cohorts. 34,402 seizures (paediatric:M=101,SD=103, adult:M=107,SD=156) were analysed and seizure cycles were grouped according to circadian (0.5-1.5 days), about-weekly (2-12 days), about-fortnightly (13-22 days) and about-monthly (23-32 days) periodicities. Significant cycles were identified in each cycle group, with no differences in prevalence or cycle strength between paediatric and adult cohorts for any multiday cycle group. Similar effects were observed across clinical and demographic features (sex, epilepsy-type, medication). These multiday patterns formed the basis for cycle-based estimates of seizure likelihood. Receiver operating characteristic (area under the curve: AUC) was applied and demonstrated that these seizure forecasts performed better than chance (i.e. shuffled seizure times). Multiday seizure cycles are therefore similar in paediatric and adult cohorts, and this study provides the first validation of cycle-based seizure risk forecasting models as a promising approach for paediatric epilepsy.

Publisher

Cold Spring Harbor Laboratory

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