Synchrony is a robust iEEG biomarker for antiseizure medication load in epileptic patients

With new, minimally invasive continuous EEG and wearable monitoring systems for epilepsy nearing regulatory approval, there is a rush to determine how to make these devices most useful to patients. One application is to track biomarkers of antiseizure medication (ASM) levels to help manage seizure risk and side effects. In this paper, we validate one such biomarker, phase synchronization, during medication taper and presurgical evaluation in a cohort of 80 consecutive patients recorded with intracranial EEG (iEEG) at the University of Pennsylvania. While previous investigators have demonstrated that synchrony is negatively correlated with ASM load at the resolution of 1 day, we hypothesize that synchrony continuously tracks and can predict ASM load on a clinically useful time scale. We test this hypothesis using a pharmacokinetic model generating continuous ASM load values previously published by our group and correlate it with continuous synchrony values derived from the iEEG. We use a linear mixed effect model to examine the relationship between ASM load, synchrony, vigilance, and other time dependent factors. We use dominance analysis to rank the relative importance of predictors based on their influence on ASM load. We find that synchrony not only can predict ASM load but is also the most significant predictor. Our study highlights the potential of synchrony as a biomarker for ASM load, and its utility in an ambulatory implantable device that can alert patients to conditions lowering their medications (e.g., adherence, drug interactions, generic change, pregnancy, etc.) or potential medication toxicity. We propose that measures like synchrony, packaged in an appropriate interface, could bring substantial value to ambulatory epilepsy management devices.