Active clinical trials for "Epilepsy"

The identification of the epileptogenic zone (EZ) during pharmacoresistant focal epilepsy presurgical assessment frequently requires intracranial recordings like stereo-electroencephalography (SEEG). Cortical direct electrical stimulation (DES) is commonly used during SEEG for functional mapping or to induce seizure. However, the recording of seizures is sometimes insufficient to circumscribe the EZ and development of new biomarkers is necessary. The cortex within the EZ is thought to be hyperexcitable. The "paired pulses" paradigm, using transcranial magnetic stimulation (TMS), allows determining the hemispheric cortical excitability level. The investigators hypothesize that paired pulses DES during SEEG could provide useful information for EZ identification.

The primary goal of this observational study is to establish the accuracy of CNS-specific Assay for Recurrent Paroxysmal Events (CARPE) as a diagnostic blood test for epilepsy. The target population is patients who have been newly referred to the Penn Epilepsy Center or patients who are admitted to HUP for continuous video EEG monitoring. (Subjects without an epilepsy diagnosis will be included.) Subjects will be asked to provide consent, agree to allow the study team to collect information from their medical record, and to provide at least one blood sample.

This observational study aims to investigate how VIMPAT® is used as adjunctive therapy in clinical practice and will also evaluate the subsequent change in the drug load of patients after addition of VIMPAT® to their treatment regimen.

This study will help describe how the human brain works when a person sees something, hears something, learns something, or thinks about something by recording brain activity that occurs when the person does a series of computer tasks. This study will be offered to people who are in the hospital to be monitored for epilepsy by using electrodes placed in the brain. The study will record brain activity that occurs when a patient does a memory task, for example.

The investigators are developing a questionnaire that can quickly measure the impact that epilepsy has on a person's life. This questionnaire will be useful in following whether the impact of epilepsy increases, decreases or stays the same over time. The results also may point out areas that would benefit from discussion or attention in visits with your doctor.

Seizure-related cardiac arrhythmias are one of the possible causes of sudden unexpected death in epilepsy (SUDEP). Identification of these patients is challenging because cardiac rhythm disturbances could emerge only during seizures. Furthermore, patients could have transitioned sinus or AV node blocks which could cause syncopes with brady-related seizures which could be treated as epilepsy-related seizures. Implantable loop recorders have an ability to recording single-channel ECG for up to 36 months which give an ability to detect these heart disturbances. The purpose of this study is to look the incidence and types of arrhythmias which occur in 150 patients with hard-to-treat partial seizures and secondarily generalized seizures

Generalized epilepsy is rarely reported in patients with Wilson disease (WD) and lacks experience in clinical practice. We aim to provide better experience for the diagnosis and treatment for WD patients with epilepsy in the future.

This is a GWAS study that aims to identify possible candidate genes associate to epilepsy by exploring single nucleotide polymorphism (SNP) in a group of epilepsy, in the Kazakh population. The investigators hypothesize that the careful phenotyping of the subject sand matching with increase the power to find SNP significantly associate with epilepsy

Epileptic patients are plighted with limited daily activities, social dysfunction, family conflicts and cognitive impairment. Most of the studies had showed that cognitive disorders were frequent in patients with epilepsy.The cognitive impairment has been reported in around 25% of epileptic patients.

Increased computational power has made it possible to implement complex image recognition tasks and machine learning to be implemented in every day usage. The computer vision and machine learning based solution used in this project (Nelli) is an automatic seizure detection and reporting method that has a CE mark for this specific use. The present study will provide data to expand the utility and detection capability of NELLI and enhance the accuracy and clinical utility of automated computer vision and machine learning based seizure detection.