Priorización del seguimiento de personas con sospecha de epilepsia mediante un biomarcador digital de EEG

Lengthy waits for follow-up testing are common for people with suspected epilepsy. This delays diagnosis, prolongs uncertainty and increases seizure risk. Initial EEGs are frequently inconclusive, yet follow-ups are often dictated by referral date, and there is no established method for risk-based prioritisation. Here, we tested whether an established digital EEG biomarker could help prioritise those most likely to have epilepsy for expedited follow-up EEG testing. We analysed 196 normal non-contributory (non-diagnostic) initial EEGs collected from six National Health Service (NHS) sites in England. From these recordings, we extracted eight previously validated computational features that quantify the likelihood that the EEG was recorded from someone with active epilepsy. We then used this information to reorder follow-up lists and compared outcomes against standard referral-based scheduling. We found that ordering for follow-up testing based upon the digital biomarker consistently prioritised people subsequently diagnosed with epilepsy; for a waitlist of 40 patients, the median number of follow-up EEGs needed to see 50% of true epilepsy patients was decreased by 6 (95% CI 4-7). The EEG diagnostic yield for epilepsy of follow-ups was increased relative to orderings based on time of referral (median increase in yield for epilepsy at 50% follow-up EEGs was 5%; 95 CI 4.9%-10%). Our study indicates that a routine EEG may furnish an objective risk metric that could accelerate second-line investigations and so reduce diagnostic delay whilst improving resource allocation in clinical practice.