Treatment of epilepsy in China: Formal or informal

Sociodemographic factors associated with the first administration of anti-seizure medication in patients with focal epilepsy in Western China

Background

Epilepsy is a severe chronic neurologic disease with a prevalence of 0.7% worldwide; anti-seizure medications (ASMs) are the mainstay of epilepsy treatment. The effects of sociodemographic factors on the characteristics of initial treatment in patients with newly diagnosed focal epilepsy in Western China are unknown. This study was conducted to explore sociodemographic factors associated with initial treatment characteristics.

Methods

Patients with focal epilepsy on continuous ASM treatment who visited to our epilepsy center at Sichuan Provincial People’s Hospital between January 2018 and December 2019 were recruited. Data on initial treatment status and sociodemographic variables were obtained from the patients with a questionnaire designed by our researchers. We examined whether sociodemographic factors were associated with epileptic patients’ access to neurologists and prescriptions of individual ASMs.

Results

A total of 569 patients completed this study. We found that patients with a higher education level, aged < 16 years, and with a higher household disposable income were more likely to receive treatment from a neurologist than their counterparts. Patients with a lower personal income level and who were treated at a junior hospital were more likely to receive prescriptions for carbamazepine, and those who were younger than 16 years were less likely to receive prescriptions for carbamazepine and oxcarbazepine. Patients with a higher education level, with a higher household disposable income level, who were younger than 16 years, and who were treated at a senior hospital were more likely to receive prescriptions for levetiracetam than their counterparts. Adult, female patients with focal epilepsy treated at a senior hospital were more likely to receive prescriptions for lamotrigine.

Conclusions

This observation suggests that sociodemographic characteristics are associated with access to neurologists and prescriptions of individual antiepileptic drugs. These data may help public health officials establish guidelines for doctors and distribute resources according to the needs of different patient groups.

Detection of epileptic seizure based on entropy analysis of short-term EEG

Entropy measures that assess signals’ complexity have drawn increasing attention recently in biomedical field, as they have shown the ability of capturing unique features that are intrinsic and physiologically meaningful. In this study, we applied entropy analysis to electroencephalogram (EEG) data to examine its performance in epilepsy detection based on short-term EEG, aiming at establishing a short-term analysis protocol with optimal seizure detection performance. Two classification problems were considered, i.e., 1) classifying interictal and ictal EEGs (epileptic group) from normal EEGs; and 2) classifying ictal from interictal EEGs. For each problem, we explored two protocols to analyze the entropy of EEG: i) using a single analytical window with different window lengths, and ii) using an average of multiple windows for each window length. Two entropy methods—fuzzy entropy (FuzzyEn) and distribution entropy (DistEn)–were used that have valid outputs for any given data lengths. We performed feature selection and trained classifiers based on a cross-validation process. The results show that performance of FuzzyEn and DistEn may complement each other and the best performance can be achieved by combining: 1) FuzzyEn of one 5-s window and the averaged DistEn of five 1-s windows for classifying normal from epileptic group (accuracy: 0.93, sensitivity: 0.91, specificity: 0.96); and 2) the averaged FuzzyEn of five 1-s windows and DistEn of one 5-s window for classifying ictal from interictal EEGs (accuracy: 0.91, sensitivity: 0.93, specificity: 0.90). Further studies are warranted to examine whether this proposed short-term analysis procedure can help track the epileptic activities in real time and provide prompt feedback for clinical practices.