A Prospective Diagnostic Belief Updating Study to verIfy the Utility of BioEP in First Seizure Clinics.

The accurate diagnosis and prognosis of epilepsy represents a significant unmet medical need. Due to the unpredictable nature of seizures, epilepsy is difficult to diagnose and treat. In the United Kingdom (UK), 125,000 people per annum are referred to first seizure clinics with suspected epilepsy of which 40,000 receive a confirmed diagnosis of epilepsy. Although diagnosing a patient with epilepsy is a clinical decision, clinicians often look towards diagnostic tests (such as electroencephalograms - EEGs) to support their decision-making process. At present, in the absence of observable epileptiform abnormalities (abnormal wave forms strongly associated with epilepsy on EEG, there are no clinically robust markers of epilepsy. Mathematical models provide a powerful and useful tool with which to identify and understand biological mechanisms that may lead to the risk of having seizures. By combining mathematical and computational techniques, Neuronostics have developed a biomarker called BioEP. Using properties in the background and clinically non contributary EEG, the investigators have demonstrated in retrospective, multi-site phase I and phase II studies sufficient evidence that could support clinicians to make more informed diagnostic decisions that investigators hope will lead to better and faster decisions about patients' diagnosis and treatment. The investigators will now conduct a prospective single site diagnostic belief updating study to examine the utility of BioEP in supporting clinicians' decision making a clinical setting in the NHS. The investigators will do this by inviting adults to take part who are suspected of having a first seizure and who will attend a first seizure clinic run by a Consultant Nurse for the Epilepsies (CNE) at the Royal Wolverhampton NHS trust. As part of the patients diagnostic work up, patients will have an EEG performed, the investigators will then apply BioEP to the patients EEG to derive a "risk score". This risk score will be presented to the CNE, who may then decide to combine it with the clinical history and clinical test information to help the CNE make decisions about patients' diagnosis and treatment.

The CNE will first rate the probability that the patient has experienced an epileptic seizure and probability of recurrence based on the clinical history and standard EEG (and any other standard tests ordered). A second assessment of this probability will be made after the CNE subsequently receives the BioEP risk score and report to quantify the updating of belief (that the patient has an increased seizure risk) and assess the utility of BioEP as a diagnostic decision support tool.