Abstract: The present disclosure relates generally to methods for determining whether a patient suffering from or at risk for STXBP1- or SYNGAP1-encephalopathy will benefit from treatment with phenylbutyrate compositions comprising screening the patient for mutations in STXBP1 or SYNGAP1. Also disclosed herein are methods for selecting patients at risk for developmental and epileptic encephalopathy (DEE) for treatment with compositions including phenylbutyrate.

Abstract: Systems, methods and programs for processing EEG data for display and/or automatically detecting a seizure in a patient based on one or more spectrograms created from the EEG data. EEG data from a patient may be paired into channels based on electrode locations. Spectrograms are generated from EEG data from channels, respectively. The spectrograms of different channels are grouped and a median power spectrogram (MPS) is calculated for the group. The MPS may be used to automatically determine whether the patient had a seizure by applying a machined learned model (ML) model. The ML model is trained and tested using historical EEG data from a plurality of patients. The MPS or a relationship between a plurality of MPS of different groups may be displayed on a bedside monitor in real-time for viewing by a bedside clinician.