Quantitative EEG findings and response to treatment with antiepileptic medications in children with epilepsy.

BACKGROUND: Epilepsy is a common chronic disorder in pediatric neurology. Nowadays, a variety of antiepileptic drugs (AEDs) are available. A scientific method designed to evaluate the effectiveness of AEDs in the early stage of treatment has not been reported. PURPOSE: In this study, we try to use quantitative EEG (QEEG) analysis as a biomarker to evaluate therapeutic effectiveness. METHODS: 20 epileptic children were enrolled in this study. Participants were classified as effective if they achieved a reduction in seizure frequency over 50%. Ineffective was defined as a reduction in seizure frequency less than 50%. Eleven participants were placed in the effective group, the remaining 9 participants were placed in the ineffective group. EEG segments before and after 1-3months of antiepileptic drugs start/change were analyzed and compared by QEEG analysis. The follow-up EEG segments after the 2nd examinations were used to test the accuracy of the analytic results. RESULTS: Six crucial EEG feature descriptors were selected for classifying the effective and ineffective groups. Significantly increased RelPowAlpha_avg_AVG, RelPowAlpha_snr_AVG, HjorthM_avg_AVG, and DecorrTime_snr_AVG values were found in the effective group as compared to the ineffective group. On the contrary, there were significantly decreases in DecorrTime_std_AVG, and Wavelet_db4_EnergyBand_5_avg_AVG values in the effective group as compared to the ineffective group. The analyses yielded a precision rate of 100%. When the follow-up EEG segments were used to test the analytic results, the accuracy was 83.3%. CONCLUSION: The developed method is a useful tool in analyzing the effectiveness of antiepileptic drugs. This method may assist pediatric neurologists in evaluating the efficacy of AEDs and making antiepileptic drug adjustments when managing epileptic patients in the early stage.