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

Epileptic Disord. 2022 Apr 1;24(2):315-322. doi: 10.1684/epd.2021.1392.


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.

Keywords: EEG; idiopathic generalized epilepsy; long-term therapeutic outcome; machine learning; semiology; typical absence seizure.

MeSH terms

  • Automatism
  • Electroencephalography
  • Epilepsy, Absence* / drug therapy
  • Humans
  • Predictive Value of Tests
  • Seizures / drug therapy