Ethosuximide, sodium valproate or lamotrigine for absence seizures in children and adolescents

Current state of the epilepsy drug and device pipeline

The field of epilepsy has undergone substantial advances as we develop novel drugs and devices. Yet considerable challenges remain in developing broadly effective, well-tolerated treatments, but also precision treatments for rare epilepsies and seizure-monitoring devices. We summarize major recent and ongoing innovations in diagnostic and therapeutic products presented at the seventeenth Epilepsy Therapies & Diagnostics Development (ETDD) conference, which occurred May 31 to June 2, 2023, in Aventura, Florida. Therapeutics under development are targeting genetics, ion channels and other neurotransmitters, and many other potentially first-in-class interventions such as stem cells, glycogen metabolism, cholesterol, the gut microbiome, and novel modalities for delivering electrical neuromodulation.

Detection method of absence seizures based on Resnet and bidirectional GRU

Background

Epilepsy is a common chronic neurological disease. Its repeated seizure attacks have a great negative impact on patients’ physical and mental health. The diagnosis of epilepsy mainly depends on electroencephalogram (EEG) signals detection and analysis. There are two main EEG signals detection methods for epilepsy. One is the detection based on abnormal waveform, the other is the analysis of EEG signals based on the traditional machine learning. The feature extraction method of the traditional machine learning is difficult to capture the high-dimension information between adjacent sequences.

Methods

In this paper, redundant information was removed from the data by Gaussian filtering, downsampling, and short-time Fourier transform. Convolutional Neural Networks (CNN) was used to extract the high-dimensional features of the preprocessed data, and then Gate Recurrent Unit (GRU) was used to combine the sequence information before and after, to fully integrate the adjacent information EEG signals and improve the accuracy of the model detection.

Results

Four models were designed and compared. The experimental results showed that the prediction model based on deep residual network and bidirectional GRU had the best effect, and the test accuracy of the absence epilepsy test set reached 92%.

Conclusions

The prediction time of the network is only 10 sec when predicting four-hour EEG signals. It can be effectively used in EEG software to provide reference for doctors in EEG analysis and save doctors’ time, which has great practical value.

Genetic generalized epilepsies in adults - challenging assumptions and dogmas

Genetic generalized epilepsy (GGE) syndromes start during childhood or adolescence, and four commonly persist into adulthood, making up 15-20% of all cases of epilepsy in adults. These four GGE syndromes are childhood absence epilepsy, juvenile absence epilepsy, juvenile myoclonic epilepsy and epilepsy with generalized tonic-clonic seizures alone. However, in ~20% of patients with GGE, characteristics of more than one syndrome are present. Novel insights into the genetic aetiology, comorbidities and prognosis of the GGE syndromes have emerged and challenge traditional concepts about these conditions. Evidence has shown that the mode of inheritance in GGE is mostly polygenic. Neuropsychological and imaging studies indicate similar abnormalities in unaffected relatives of patients with GGE, supporting the concept that underlying alterations in bilateral frontothalamocortical networks are genetically determined. Contrary to popular belief, first-line anti-seizure medication often fails to provide seizure freedom in combination with good tolerability. Nevertheless, long-term follow-up studies have shown that with advancing age, many patients can discontinue their anti-seizure medication without seizure relapses. Several outcome predictors have been identified, but prognosis across the syndromes is more homogeneous than previously assumed. Overall, overlap in pathophysiology, seizure types, treatment responses and outcomes support the idea that GGEs are not separate nosological entities but represent a neurobiological continuum.