Quantitative EEG analysis in typical absence seizures: unveiling spectral dynamics and entropy patterns.

A typical absence seizure is a generalized epileptic event characterized by a sudden, brief alteration of consciousness that serves as a hallmark for various generalized epilepsy syndromes. Distinguishing between similar interictal and ictal electroencephalographic (EEG) epileptiform patterns poses a challenge. However, quantitative EEG, particularly spectral analysis focused on EEG rhythms, shows potential for differentiation. This study was designed to investigate discernible differences in EEG spectral dynamics and entropy patterns during the pre-ictal and post-ictal periods compared to the interictal state. We analyzed 20 EEG ictal patterns from 11 patients with confirmed typical absence seizures, and assessed recordings made during the pre-ictal, post-ictal, and interictal intervals. Power spectral density (PSD) was used for the quantitative analysis that focused on the delta, theta, alpha, and beta bands. In addition, we measured EEG signal regularity using approximate (ApEn) and multi-scale sample entropy (MSE). Findings demonstrate a significant increase in delta and theta power in the pre-ictal and post-ictal intervals compared to the interictal interval, especially in the posterior brain region. We also observed a notable decrease in entropy in the pre-ictal and post-ictal intervals, with a more pronounced effect in anterior brain regions. These results provide valuable information that can potentially aid in differentiating epileptiform patterns in typical absence seizures. The implications of our findings are promising for precision medicine approaches to epilepsy diagnoses and patient management. In conclusion, our quantitative analysis of EEG data suggests that PSD and entropy measures hold promise as potential biomarkers for distinguishing ictal from interictal epileptiform patterns in patients with confirmed or suspected typical absence seizures.

Electroclinical features and long-term therapeutic response in patients with typical absence seizures.

OBJECTIVE: To characterize in detail the electroclinical features of typical absence seizures and elucidate whether EEG or semiology features, alone or in combination, can predict long-term therapeutic outcome. METHODS: We analysed video-EEG recordings from 213 typical absence seizures from 61 patients with idiopathic generalized epilepsy. We extracted semiological features, in addition to hallmark manifestations (motor/behavioural arrest, non-responsiveness), their location, timing and frequency. We evaluated the duration and frequency of generalized spike-wave discharges and the presence of polyspikes. We used a supervised machine-learning approach (random forest) to search for classifier features for long-term therapeutic outcome (>one year). RESULTS: Besides the hallmark manifestations, additional semiological features were identified in 87% of patients (75% of seizures). The most common additional semiological features were automatisms and eye blinking (observed in 45% and 41.5% of seizures, respectively). Automatisms were associated with longer seizure duration, and oral automatisms occurred earlier compared to limb automatisms (4.03 vs. 6.19 seconds; p=0.005). The mean duration of the ictal spike-wave discharges was nine seconds, and the median frequency was 3 Hz. Polyspikes occurred in 46 seizures (21.6%), in 19 patients (31%). Median follow-up was five years, and 73% of the patients were seizure-free at the end of the follow-up. None of the semiological features, alone or in combination, were predictors of therapeutic outcome. The only significant classifier was the presence of polyspikes, predicting a non-seizure-free outcome with an accuracy of 73% (95% CI: 70-77%), positive predictive value of 92% (95% CI: 84-98%) and negative predictive value of 60% (95% CI: 39-81%). SIGNIFICANCE: Semiological features, in addition to behavioural arrest and non-responsiveness, are common in typical absence seizures, but they do not predict long-term therapeutic outcome. The presence of polyspikes has a high positive predictive value for unfavourable therapeutic outcome, and their presence should therefore be included when reporting EEGs in patients with typical absence seizures.

High-power, frontal-dominant ripples in absence status epilepticus during childhood.

OBJECTIVE: Absence status epilepticus (ASE) is a form of non-convulsive status epilepticus characterized by ongoing or intermittent epileptic activity accompanied by behavioral and cognitive changes. Herein, we assessed high-frequency oscillations in the ripple band in patients with ASE and typical absence seizures. METHODS: We enrolled five patients with ASE, 26 patients with childhood absence epilepsy (CAE), and 15 patients with juvenile absence epilepsy (JAE). We performed time-frequency analysis of electroencephalogram data for ictal absence seizures at each electrode to assess the high frequency activity (HFA) rate, peak frequency, and peak power. RESULTS: The average HFA rates were 60.7%, 20.8%, and 12.9% in ASE, CAE, and JAE patients, respectively. The average peak frequencies were 126.4 Hz, 120.9 Hz, and 126.1 Hz in ASE, CAE, and JAE patients, respectively. The average peak power values were 2,388.8 µV2, 120.9 µV2, and 126.1 µV2 in ASE, CAE, and JAE patients, respectively, and all epilepsy groups exhibited frontal-dominant ripple distribution. CONCLUSION: ASE patients presented higher power and frontal dominant ripples of absence seizure, compared to CAE and JAE patients. SIGNIFICANCE: Future studies should utilize scalp-recorded ripples as a biomarker of absence epilepsy. This may aid in the development of novel treatment strategies for ASE.

Myoclonic jerks are commonly associated with absence seizures in early-onset absence epilepsy.

Typical absence seizures are observed in various epilepsy syndromes, however, few series have focused on early-onset absence epilepsy (EOAE). We aimed to evaluate the occurrence of this seizure type in children under 4 years of age in order to evaluate their electroclinical characteristics and outcome. We retrospectively studied (2006-2014) the electroclinical features of children with normal development and typical absence seizures starting before the age of 4 (with available pre-treatment video-EEG). Nine patients were included. Among them, eight patients had rhythmic myoclonic jerks involving the muscles of the upper face (eyebrows and eyelids) or neck, present from the onset to the end of the typical absence discharge. The myoclonia were synchronous with spike-wave complexes. One patient with GLUT-1 deficiency was refractory to antiepileptic polytherapy. The other eight became seizure-free; five with one antiepileptic drug and three with a combination of two drugs. The treatment was successfully withdrawn in five of the six patients who achieved two years of seizure freedom. None of them exhibited any other seizure type. Four of the eight patients with normal schooling required some support. We observed a positive correlation between the duration of absence seizure and the age of the patient at examination. Most of the patients under four years with only typical absence seizures had EOAE, and the motor symptoms may represent a distinctive age-related feature of EOAE. Further investigations are required to better correlate the role of brain maturation with the duration of the absence. [Published with video sequence on www.epilepticdisorders.com].