Epilepsy & behavior reports · 2026
The electroclinical phenotype of epilepsy following autoimmune encephalitis.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Neidhart Stephan, Dubcek Tena, Ledergerber Debora, Kohnen Oona, Imbach Lukas
Аннотация
OBJECTIVE: To describe the temporal and spatial dynamics of electroencephalographic (EEG) recordings in epilepsy following autoimmune encephalitis (AE) compared to temporal lobe epilepsy (TLE) without signs of inflammatory etiology.
METHODS: We assessed electroencephalographic properties using continuous long-term (72-h) EEG recordings in combination with neuroimaging markers and cerebrospinal fluid (CSF) parameters of 25 patients with epilepsy following AE and 30 patients with TLE. We specifically investigated the presence of focal slowing (FS) and epileptiform discharges (EDs). Additionally, spectral EEG variability during wakefulness and sleep was analyzed using quantitative EEG analysis.
RESULTS: Compared to TLE, patients with AE showed significantly more independent bitemporal FS and independent bitemporal EDs (p < 0.05), with a higher co-occurrence of both patterns (p < 0.05). Quantitative analysis of wake and sleep EEG revealed greater spectral variability in AE, particularly in the temporal regions. A composite score incorporating EEG data, MRI and CSF parameters, as well as clinical features, effectively distinguished AE from TLE (p < 0.0001). Using the same variables, principal component analysis also demonstrated clear separation between the two groups.
SIGNIFICANCE: These results demonstrate distinct and quantifiable EEG characteristics in epilepsy following AE. The identified EEG patterns and the proposed score may serve as biomarkers for differentiating between epilepsy following AE and TLE of non-inflammatory etiology. This approach can aid clinicians in determining the need for further diagnostic testing or optimizing therapy decisions in the post-acute phase, where clinicians frequently encounter patients with new-onset or evolving epilepsy in whom a current or prior inflammatory etiology is suspected. In this scenario, a precise understanding of post-acute EEG characteristics may be clinically relevant to assess the probability of an underlying autoimmune/inflammatory process and to guide the immune-directed evaluation, antiseizure medication optimization, and epilepsy-surgical evaluation.
METHODS: We assessed electroencephalographic properties using continuous long-term (72-h) EEG recordings in combination with neuroimaging markers and cerebrospinal fluid (CSF) parameters of 25 patients with epilepsy following AE and 30 patients with TLE. We specifically investigated the presence of focal slowing (FS) and epileptiform discharges (EDs). Additionally, spectral EEG variability during wakefulness and sleep was analyzed using quantitative EEG analysis.
RESULTS: Compared to TLE, patients with AE showed significantly more independent bitemporal FS and independent bitemporal EDs (p < 0.05), with a higher co-occurrence of both patterns (p < 0.05). Quantitative analysis of wake and sleep EEG revealed greater spectral variability in AE, particularly in the temporal regions. A composite score incorporating EEG data, MRI and CSF parameters, as well as clinical features, effectively distinguished AE from TLE (p < 0.0001). Using the same variables, principal component analysis also demonstrated clear separation between the two groups.
SIGNIFICANCE: These results demonstrate distinct and quantifiable EEG characteristics in epilepsy following AE. The identified EEG patterns and the proposed score may serve as biomarkers for differentiating between epilepsy following AE and TLE of non-inflammatory etiology. This approach can aid clinicians in determining the need for further diagnostic testing or optimizing therapy decisions in the post-acute phase, where clinicians frequently encounter patients with new-onset or evolving epilepsy in whom a current or prior inflammatory etiology is suspected. In this scenario, a precise understanding of post-acute EEG characteristics may be clinically relevant to assess the probability of an underlying autoimmune/inflammatory process and to guide the immune-directed evaluation, antiseizure medication optimization, and epilepsy-surgical evaluation.