Prioritising Follow-Up for People with Suspected Epilepsy Using a Digital EEG Biomarker.

Area of Science:

• Neurology
• Biomarkers
• Medical Diagnostics

Background:

• Lengthy waits for follow-up testing are common for individuals with suspected epilepsy, leading to diagnostic delays, prolonged uncertainty, and increased seizure risk.
• Initial electroencephalograms (EEGs) are often inconclusive, and follow-up scheduling typically relies on referral date rather than individual risk assessment.

Purpose of the Study:

• To evaluate the effectiveness of a digital EEG biomarker in prioritizing patients for expedited EEG testing.
• To determine if this biomarker can improve the diagnostic yield and efficiency of epilepsy investigations.

Main Methods:

• Analysis of 196 non-diagnostic initial EEGs from six National Health Service (NHS) sites.
• Extraction of eight computational features to derive a digital biomarker quantifying epilepsy likelihood.
• Reordering of follow-up EEG lists based on the digital biomarker and comparison with standard referral-based scheduling.

Main Results:

• Prioritizing follow-up testing using the digital biomarker consistently identified individuals subsequently diagnosed with epilepsy.
• The diagnostic yield of each EEG performed increased significantly compared to standard referral-based scheduling.
• The biomarker demonstrated potential for objective risk stratification in epilepsy diagnosis.

Conclusions:

• A digital EEG biomarker can effectively prioritize patients for timely epilepsy diagnosis, reducing diagnostic delays.
• This approach enhances the efficiency of resource allocation in clinical practice by improving the diagnostic yield of follow-up EEGs.
• Routine EEGs can provide objective risk metrics to expedite second-line investigations for suspected epilepsy.