Zongpu Zhou, Yue Niu, Zhao Xu, Xianru Jiao, Pan Gong, Genfu Zhang, Ang Ma, Yuehua Zhang, Jiong Qin, Zhixian Yang
Patients with MT seizures can be categorized into distinct groups based on electro-clinical features. EMTS exhibits a distinct electro-clinical profile and a favorable prognosis. MT seizures appear to be a key biomarker identifying this patient subset, warranting further validation as a potential distinct diagnostic entity.
BACKGROUND: Myoclonic-tonic (MT) seizures are characterized by a preceding period of myoclonus followed closely by the occurrence of tonic seizures. The objective of this study was to dissect the electro-clinical features of patients with MT seizures.
METHODS: We conducted a retrospective analysis of patients with MT seizures, including symptomatic and electrographic characteristics of the seizures, clinical background, diagnoses, and prognosis. Latent class analysis and quantitative electroencephalograph analysis were employed to identify distinct subtypes of epilepsy among enrolled patients.
RESULTS: MT seizures can be observed across a disease spectrum ranging from unclassified generalized epilepsy to developmental and epileptic encephalopathy. Latent class analysis revealed two distinct classes. Class 2 exhibited an earlier age of epilepsy onset, higher rates of intellectual disability, and resistance to anti-seizure medication than Class 1. Class 1 primarily comprised a cohort of patients with generalized epilepsy that did not meet criteria for any named syndromes; we defined it as epilepsy with myoclonic-tonic seizures (EMTS). EMTS displayed typically normal background activity, well-developed cognition, and relatively high rates of seizure freedom. The EMTS group exhibited lower relative power in the alpha and beta bands and lower spectral edge frequency than the Lennox-Gastaut syndrome group.
CONCLUSIONS: Patients with MT seizures can be categorized into distinct groups based on electro-clinical features. EMTS exhibits a distinct electro-clinical profile and a favorable prognosis. MT seizures appear to be a key biomarker identifying this patient subset, warranting further validation as a potential distinct diagnostic entity.