Work

Tracking seizure cycles beats a prospective moving average: Commentary on "Rigorous evaluation of five e‐diary alone seizure forecasting tools"

Year: 2025

Type: article

Abstract: There is debate on the predictive value of multiday seizure cycles versus simple statistical baselines. Multidien seizure cyclicity is a prevalent, patient-specific phenomenon with promise for epilepsy management. We challenge the assertion that cycle tracking is no better than a moving average, which is an inherently retrospective model that lags changes in seizure likelihood. This commentary compared a causal cyclic forecast to a prospectively applied moving average across a large seizure diary cohort (n = 768) and two gold-standard chronic EEG cohorts (n = 24). For the EEG and diary cohorts, cycle tracking demonstrated significantly superior accuracy to the moving average for both hourly and daily forecasts (p < 0.0001), using multiple performance metrics. These results confirm that event-based cyclical models offer more accurate, simulated real-world forecasts. Robust forecasting tools must prioritize the detection and modeling of seizure cycles to move beyond simple baseline performance and provide actionable clinical utility.

Source: Epilepsia

DOI: 10.1002/epi.70084

Authors: Rachel E. Stirling, Benjamin H. Brinkmann, Dean R. Freestone, Philippa J. Karoly

Institutions: The University of Melbourne, Mayo Clinic

Language: English

Topic: Epilepsy research and treatment

Subfield: Psychiatry and Mental health

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: bronze

Funders: Medical Research Council, National Health and Medical Research Council