The risk of developing epilepsy in people who had febrile seizures seems to decrease with time. Further long-term studies are needed to confirm this.

No abstract

Background: Rapidly progressive dementia (RPD) is a clinical syndrome developing in <1 to 2 years. Recent progress in RPD evaluation is significant, so RPD’s prevalence may change over time. The aim of our new case series was to estimate the relative frequency of RPDs’ causative entities, considering the recent advances in RPDs’ diagnosis, and compare the results with those of our previous report. Patients and Methods: We retrospectively reviewed the medical records of 47 patients who were referred to Attikon University Hospital during a 5-year period for a suspected RPD. Results: Neurodegenerative diseases were the most frequent causes (38%), followed by prion disease (19%) and autoimmune encephalopathy (AE, 17%). AE cases were by far more common than in our previous report, while other than AE secondary causes were significantly decreased. Mean time to dementia was 9 months in neurodegenerative diseases and 5 months in non-neurodegenerative. Main clinical findings across all patients were memory impairment (66%) and behavioral-emotional disturbances (48%). Conclusions: Neurodegenerative diseases are common causes of RPD and have a slower evolution than non-neurodegenerative. Diagnostic novelties enabled the recognition of AE, whereas more common secondary causes are probably now diagnosed in primary settings since the recognition of RPD as distinct clinical entity is continually increasing.

Abnormal EEG features are a hallmark of epilepsy, and abnormal frequency and network features are apparent in EEGs from people with idiopathic generalised epilepsy in both ictal and interictal states. Here, we characterise differences in the resting-state EEG of individuals with juvenile myoclonic epilepsy and assess factors influencing the heterogeneity of EEG features. We collected EEG data from 147 participants with juvenile myoclonic epilepsy through the Biology of Juvenile Myoclonic Epilepsy study. 95 control EEGs were acquired from two independent studies (Chowdhury et al. (2014) and EU-AIMS Longitudinal European Autism Project). We extracted frequency and functional network-based features from 10-20 s epochs of resting-state EEG, including relative power spectral density, peak alpha frequency, network topology measures and brain network ictogenicity: a computational measure of the propensity of networks to generate seizure dynamics. We tested for differences between epilepsy and control EEGs using univariate, multivariable and receiver operating curve analysis. Additionally, we explored the heterogeneity of EEG features within and between cohorts by testing for associations with potentially influential factors such as age, sex, epoch length and time, as well as testing for associations with clinical phenotypes including anti-seizure medication, and seizure characteristics in the epilepsy cohort. P-values were corrected for multiple comparisons. Univariate analysis showed significant differences in power spectral density in delta (2-5 Hz) (p = 0.0007, hedges’ g = 0.55) and low-alpha (6-9 Hz) (p = 2.9 × 10−8, g = 0.80) frequency bands, peak alpha frequency (p = 0.000007, g = 0.66), functional network mean degree (p = 0.0006, g = 0.48) and brain network ictogenicity (p = 0.00006, g = 0.56) between epilepsy and controls. Since age (p = 0.009) and epoch length (p = 1.7 × 10−8) differed between the two groups and were potential confounders, we controlled for these covariates in multivariable analysis where disparities in EEG features between epilepsy and controls remained. Receiver operating curve analysis showed low-alpha power spectral density was optimal at distinguishing epilepsy from controls, with an area under the curve of 0.72. Lower average normalized clustering coefficient and shorter average normalized path length were associated with poorer seizure control in epilepsy patients. To conclude, individuals with juvenile myoclonic epilepsy have increased power of neural oscillatory activity at low-alpha frequencies, and increased brain network ictogenicity compared to controls, supporting evidence from studies in other epilepsies with considerable external validity. In addition, the impact of confounders on different frequency-based and network-based EEG features observed in this study highlights the need for careful consideration and control of these factors in future EEG research in idiopathic generalised epilepsy particularly for their use as biomarkers.

Generic versus branded antiepileptic drug monotherapy for epilepsy (Protocol).