Individualized Prediction of Drug Resistance in People with Post-Stroke Epilepsy: A Retrospective Study

J Clin Med. 2023 May 23;12(11):3610. doi: 10.3390/jcm12113610.

Abstract

Background: The study aimed to develop a model and build a nomogram to predict the probability of drug resistance in people with post-stroke epilepsy (PSE).

Methods: Subjects with epilepsy secondary to ischemic stroke or spontaneous intracerebral hemorrhage were included. The study outcome was the occurrence of drug-resistant epilepsy defined according to International League Against Epilepsy criteria.

Results: One hundred and sixty-four subjects with PSE were included and 32 (19.5%) were found to be drug-resistant. Five variables were identified as independent predictors of drug resistance and were included in the nomogram: age at stroke onset (odds ratio (OR): 0.941, 95% confidence interval (CI) 0.907-0.977), intracerebral hemorrhage (OR: 6.292, 95% CI 1.957-20.233), severe stroke (OR: 4.727, 95% CI 1.573-14.203), latency of PSE (>12 months, reference; 7-12 months, OR: 4.509, 95% CI 1.335-15.228; 0-6 months, OR: 99.099, 95% CI 14.873-660.272), and status epilepticus at epilepsy onset (OR: 14.127, 95% CI 2.540-78.564). The area under the receiver operating characteristic curve of the nomogram was 0.893 (95% CI: 0.832-0.956).

Conclusions: Great variability exists in the risk of drug resistance in people with PSE. A nomogram based on a set of readily available clinical variables may represent a practical tool for an individualized prediction of drug-resistant PSE.

Keywords: brain infarct; cerebral hemorrhage; nomogram; seizures; stroke.

Grants and funding

This research received no external funding.