Research progress on the prediction of post-stroke epilepsy

Abstract

AbstractEpilepsy is a common neurological disease that not only causes difficulties in the work and life activities of patients, but also brings complex social problems. Cerebrovascular disease is currently the main cause of epilepsy in the elderly. With the increased survival rate of patients after stroke, the incidence of epilepsy after stroke has also increased. Effective prediction of epilepsy after stroke is extremely crucial for the prognosis of patients, the initiation of antiepileptic therapy and the reduction of epileptic seizures. In this review, we summarize and compare the current models for the prediction of epilepsy after stroke, including the SeLECT prediction model, Post-Stroke Epilepsy Risk Scale (PoSERS), CAVE score, electroencephalogram (EEG) prediction model, and Scandinavian Stroke Scale (SSS) score, in order to provide reference for clinical practice and future research. Prediction models can be selected based on the clinical classification of cerebrovascular events. The SeLECT score prognostic model is a better choice for ischemic stroke, especially for the exclusive prediction of mild post stroke epilepsy. The CAVE score model is suitable for intra-cerebral hemorrhage patients. It is simple and offers high correlation between the risk factors and epilepsy. The PoSERS score simultaneously predicts ischemic and hemorrhagic stroke, and is superior to other methods in specificity as well as positive and negative prediction rate. The SSS score, which only measures stroke severity, is not strictly considered as a mature predictor, but it can be used as a first step screening tool. A growing number of large studies are under the way to identify risk factors of poststroke epilepsy (PSE) and to improve the inclusion of predictive indicators. New and advanced findings by EEG recordings may further improve the prediction of PSE.