Invasive EEG for temporal lobe epilepsy: selection of technique

Guzeeva, A.S.; Amelina, Evgeniya; Халепа, Анастасия Анатольевна; Дмитриев, А. Б.; Denisova, Natalia; Рзаев, Д. А.

doi:10.17116/neiro20218505123

Cited by 3 publications

(1 citation statement)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Relevant clinical research reports [ 15 ] that in the case of acute pathological damage to the cerebral cortex, electrolyte, neuronal ischemia, acid-base balance disorder, and hypoxia will be accompanied, which will greatly affect the stability of neuron cells, and obvious depolarization will further affect the activity of cortical neurons [ 16 ]. When the electrical activity spreads to the adjacent tissues, it will stimulate the thalamus greatly and produce an excitatory transient postsynaptic potential, which will then activate the distal or adjacent neuron groups and significantly change the neural network [ 17 ]. These mechanisms are consistent with the results of this study [ 18 ].…”

Section: Discussionmentioning

confidence: 99%

Prediction Value of Epilepsy Secondary to Inferior Cavity Hemorrhage Based on Scalp EEG Wave Pattern in Deep Learning

Jiang

2022

Journal of Healthcare Engineering

View full text Add to dashboard Cite

Objective. To search the predictive value of epilepsy secondary to acute subarachnoid hemorrhage (aSAH) based on EEG wave pattern in deep learning. Methods. A total of 156 cases of secondary epilepsy with lower cavity hemorrhage in our hospital were selected and divided into the late epilepsy group and the early epilepsy group according to seizure time, and the nonseizure group and the seizure group according to seizure condition. General data of patients were collected, the EEG types of each group were analyzed, and the disease recurrence rate, treatment effect, and symptom onset time were compared. Results. Rapid and slow and rapid blood flow velocity were the main abnormal manifestations of epilepsy secondary to inferior cavity hemorrhage, accounting for 33.3% and 18.6%, respectively. Compared with the seizure group, the proportion of type ii and type iii in the nonseizure group was higher, and the proportion of type ii and type iii in the early epilepsy group was higher than in the late epilepsy group ( P < 0.05). The diagnostic accuracy, missed diagnosis rate, misdiagnosis rate, specificity, and sensitivity of the EEG wave pattern were 94.9%, 3.2%, 1.9%, 91.7%, and 96.2%, respectively. Compared with the early epilepsy group, the recurrence rate of type iii and type iv in the late epilepsy group was higher ( P < 0.05). The effective rates of the attack group and the nonattack group were 72.7% and 97.0%, respectively. Compared with the attack group, the effective rate of the nonattack group was higher ( P < 0.05). The effective rates of the early epilepsy group and the late epilepsy group were 91.7% and 85.0%, respectively. Compared with the late epilepsy group, the effective rate of the early epilepsy group was higher ( P < 0.05). Compared with the early epilepsy group, the late epilepsy group had longer tonic-clonic seizures, atonic seizures, and absent seizures, and the difference between the groups was statistically significant ( P < 0.05). Conclusion. In aSAH secondary epilepsy disease prediction, based on indepth study of the scalp EEG wave type prediction, they play an important role, including aSAH high-risk secondary epilepsy wave types for V, III, and IV types, as well as early and late epilepsy associated with disease stage. Through the diagnosis method to predict the severity of disease, this builds a good foundation for clinical treatment. It is beneficial to improve the effective rate of treatment.

show abstract