Transient epileptic amnesia (TEA) is a rare cause of acute amnestic syndromes (AAS), often misdiagnosed as transient global amnesia (TGA). We proposed a scoring system—the EPIlepsy AMNEsia (EPIAMNE) score—using quantitative EEG (qEEG) analysis to obtain a tool for differentiating TEA from TGA. We retrospectively reviewed clinical information and standard EEGs (stEEG) of 19 patients with TEA and 21 with TGA. We computed and compared Power Spectral Density, demonstrating an increased relative theta power in TGA. We subsequently incorporated qEEG features in EPIAMNE score, together with clinical and stEEG features. ROC curve models and pairwise ROC curve comparison were used to evaluate and compare the diagnostic accuracy for TEA detection of EPIAMNE score, presence of symptoms atypical for TGA (pSymAT) and identification of anomalies (interictal epileptiform or temporal focal spiky transients) at stEEG (PosEEG). Area Under the Curve (AUC) of EPIAMNE score revealed to be higher than PosEEG and pSymAT (AUCEPIAMNE = 0.95, AUCpSymAT = 0.85, AUCPosEEG = 0.67) and this superiority proved to be statistically significant (p-valueEPIAMNE-PosEEG and p-valueEPIAMNE-pSymAT < 0.05). In conclusion, EPIAMNE score classified TEA with higher accuracy than PosEEG and pSymAT. This approach could become a promising tool for the differential diagnosis of AAS, especially for early TEA detection.
Keywords: acute amnestic syndromes; quantitative EEG analysis; transient epileptic amnesia.