Seizure Onset and Recurrence Management

Seizure onset and recurrence management encompasses the identification, evaluation and treatment of individuals who experience a first seizure and those at risk of further episodes. Initial assessment centres on clinical history, neurological examination and neuroimaging to distinguish unprovoked seizures from acute symptomatic events provoked by metabolic disturbances, infection or structural lesions. Electroencephalography (EEG) plays a central role in detecting epileptiform activity, while magnetic resonance imaging and specialised imaging protocols may reveal underlying lesions or connectivity changes. Key determinants of recurrence risk include seizure semiology, EEG abnormalities, imaging findings and patient factors such as age, comorbidities and family history. Clinical decision-making balances the benefits of early antiseizure medication (ASM) against potential side effects, with risk stratification tools guiding whether to initiate therapy immediately or adopt a watch-and-wait approach. For those at low risk, monitoring and patient education may suffice, while those at medium or high risk often benefit from tailored ASM regimens and lifestyle counselling. Emerging strategies incorporate predictive modelling and machine learning to refine prognosis, support shared decision-making and optimise resource allocation. Multidisciplinary care pathways and first-seizure clinics facilitate timely diagnosis, counselling on driving restrictions and psychosocial support. Globally, improved management of seizure recurrence reduces morbidity, enhances quality of life and informs public health policies on safety, driving and workforce participation.

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Seizure Onset and Recurrence Management publication trend

The graph below shows the total number of articles in seizure onset and recurrence management across all publications each year (not limited to Nature Index journals).

Technical terms

Electroencephalography (EEG): non-invasive recording of the brain’s electrical activity via scalp electrodes.

Large language model: AI system trained on extensive text corpora to analyse and generate human-like language.

Prognostic model: statistical framework to estimate the likelihood of future clinical events based on patient data.

Antiseizure medication (ASM): pharmacological agents used to prevent or reduce the frequency of seizures.

First unprovoked seizure: an initial seizure occurring without an immediate identifiable cause or provoking factor.

References

1. Predicting seizure recurrence after an initial seizure-like episode from routine clinical notes using large language models: a retrospective cohort study. The Lancet Digital Health (2023).
2. Diagnostic value of EEG after a first unprovoked seizure in adults – A population-based study. Epilepsy & Behavior (2024).
3. Prediction begins with diagnosis: Estimating seizure recurrence risk in the First Seizure Clinic. Seizure (2024).