Objective
To summarize and analyze the clinical and video-EEG (VEEG) characteristics of adult sleep-related epilepsy, so as to provide evidence for clinical diagnosis, differential diagnosis and treatment.
Methods
The clinical data, routine EEG and long-term VEEG of 187 adult patients with sleep-related epilepsy treated in Department of Neurology, Xiangya Hospital, Central South University from January 2017 to December 2017 were retrospectively analyzed by χ2 test.
Results
Clinical manifestations: The duration of sleep-related epilepsy in 187 adults was concentrated in 1～10 years (101 cases, 54.01%); the frequency of seizures was mainly from several to dozens of times a year (99 cases, 52.94%); 119 cases (63.64%) had two or more types of seizures. Among the patients, 121 cases (39.29%) had focal origin, 152 cases (49.35%) had bilateral tonic clonus and 110 cases (58.82%) were treated with two or more drugs. EEG results: ① The detection rate of epileptiform discharges in routine EEG was 22.78%, and that in long-term video EEG was 80.43%. There was significant difference between the two methods (P< 0.01); ② Eighteen epileptiform discharges were monitored by routine EEG during interparoxysmal period and 111 epileptiform discharges were monitored by video EEG; and ③ Fifty-six epileptic events were monitored and all occurred in the process of long-term VEEG monitoring, 50 of them occurred in sleep (89.29%) and 6 in awake (10.71%); 45 cases (80.36%) were diagnosed as epileptic seizures, 9 cases (16.07%) were diagnosed as non-epileptic seizures, and 2 cases (3.57%) could not be determined. ④ The detection rate of epileptic discharges during sleep was higher than that during awake period in long-term VEEG monitoring (P< 0.01). The detection rate of epileptiform discharges in NREM stage I–II was the highest in sleep stage.
Conclusion
Sleep-related epilepsy in adults has certain clinical features and EEG manifestations. Compared with conventional EEG, long-term video-EEG can improve the detection rate of epileptiform discharges, provide diagnostic basis for the qualitative analysis of sleep-related seizures, and reflect the relationship between epileptiform discharges and sleep, and provide basis for the clinical diagnosis and treatment of sleep-related epilepsy in adults.
It is an important means to study the electrical activity of the brain's nerve cells by exploring physiological information of the EEGs from the frequency domain. The gravity frequency is one of the global parameters with using this method. We used the multitaper spectrum method (MTM) spectrum estimation method of good performance to calculate the EEG spectrum and its gravity frequency of subjects under vigilance and vigilance decrement state. The results showed that the gravity frequency of vigilance state was higher than that of vigilance decrement state, the gravity frequency became smaller along with the vigilance decrement, and the location of the gravity frequency shifted to the left in the spectrum. Finally, the monitoring curve of the gravity frequency was acquired by designing an algorithm, and it was used to online monitoring vigilance operators.
Objective
To investigate the clinical and EEG characteristics, therapeutic response and prognosis in children with atypical absence seizures.
Methods
The clinical and EEG data of 43 children with atypical absence seizures in Qilu Hospital, Shandong University during January 2011 to December 2016 were analyzed, and therapeutic response and prognosis were followed up.
Results
Childre were 24 male and 19 female with the mean age of 5.43 y. The onset ages were from 1 years and 8 months to 10 years and 3 months. All of the 43 patients had MRI examines, and 18 children were normol. MRI abnormalities appeared in 25 children, including cerebral cortical dysplasia and cerebral atrophy (13 cases), congenital corpus callosum hypoplasia (2 cases), and abnormal signal in bilateral posterior putamen (2 cases), encephalomalacia focus(4 cases), ventricle expention (2 cases), hydrocephalus(2 cases). All the children underwent EEG more than once. All children had atypical absence seizures during daytime. Children had slowly backgrounds in retesting EEG, and spine and slow waves of 1.5 Hz to 2.8 Hz could be seen in all the atypical absence seizures. All children were followed up, and except 6 children with complete control, 19 children’ parents reported seizure- free, 18 children have poor effect. Forty Children had various degrees of psychological abnormalities and motor regression. Among them 13 cases had psychological abnormalities and motor regression before disease; cognitive ability of 27 cases were normal before onset age, however, about 75% to 95% of the children became abnormal 2 years after atypical absence seizures. The rest 3 cases had no obviously impairment.
Conclusions
Most of the atypical absence seizures children had small onset age and high incidence in mental damage and cognitive impairment. The course of typical absence seizures aggravate gradually, and often develops to nonspecific brain damage in this process. Antiepileptic drugs can reduce the frequency of the seizure in part of the patients, but had no effect on psychological and motor regression.
Epilepsy has been recognized as a brain network disorder. Therefore, functional MRI (fMRI)-based connectivity is an ideal technique for exploring the complex effects of epilepsy on the brain. Functional connectivity studies have provided insights into the physiopathogenesis of the epileptic network underlying focal epilepsies, genetic generalized epilepsy, and specific epileptic syndromes. An increasing number of studies have focused on the deleterious effects of epilepsy on other brain networks to help to explain cognitive deficits and psychiatric symptoms. Anti-epileptic treatment studies have yielded information about the side effects and the restoration of functional abnormalities after using the drug. Researchers who have examined predictors of surgical outcomes have suggested that there might be identifiable pre-surgical patterns of functional connectivity that are associated with a greater likelihood of positive cognitive or seizure outcomes. However, knowledge regarding the role of fMRI connectivity remains limited in clinical settings. Further validation through invasive investigations and follow-up studies is required for its reliable application in the clinical management of individual patients. (C) 2016 Published by Elsevier Ltd on behalf of British Epilepsy Association.
ObjectiveThe purpose of this study was to investigate the autoimmune encephalitis (AE) seizure types and EEG characteristics and the value of diagnosis.
MethodsFifteen AE patients were hospitalized in the Department of Neurology at the First Hospital of Jilin University from November 2012 to July 2014. Data from their clinical manifestations, seizure types, EEG characteristics and laboratory investigation were analyzed.
ResultA total of 15 patients, 5 males and 10 females, aged 19-75 years were included. Eight cases of anti-NMDA receptor encephalitis, five cases of LGI1 receptor encephalitis and two cases of anti-Hu antibody encephalitis were diagnosed clinically.①Anti-NMDA receptor encephalitis:seven patients had seizures, which inclued complex partial seizure, generalized tonic-clonic seizure, simple partial seizure and status epilepticus.Three patients had extreme delta brush.②LGI1 receptor encephalitis:two cases had seizures, while four cases with FBDS. Sharp and slow waves with irregular delta waves appeared in bilateral temporal areas in EEG of three cases, while one case showed clinical seizure. Two cases detected "limb shaking and others" attack, but the corresponding EEG showed no abnormalities.③Anti-Hu antibody encephalitis:one case showed seizures, the EEG showed a lot of sharp and slow waves with irregular delta waves in bilateral temporal areas, while one case showed sharp and slow waves.
ConclusionAnti-NMDA receptor encephalitis can present with various types of seizures and non-convulsive status epilepticus, interictal extreme delta brush is more specific. It has important value. LGI1 receptor encephalitis is characterized by FBDS, it has important clinical significance.Anti-Hu antibody encephalitis lesions diffuse distribution, clinical manifestations are different. It may be associated with seizures, seizure types are not-specific.It may have slow waves or sharp and slow waves.
ObjectiveThe purpose of this study was to compare the value of SEEG and subdural cortical electrodes monitoring in preoperative evaluation of epileptogenic zone.
MethodsFeatures of patients using SEEG (48 cases) and subdural cortical electrodes monitoring (52 cases) to evaluate the epileptogenic zone were collected from June 2011 to June 2015. And the evaluation results, surgical effects and complications were compared.
ResultsThere was no significant difference between SEEG and subdural cortical electrodes monitoring in identifying the epileptogenic zone or taking epileptic surgery, but SEEG could monitor multifocal and bilateral epileptogenic zone. And there was no significant difference in postoperative seizure control and intelligence improvement (P > 0.05). The total complication rate of SEEG was lower than subdural cortical electrodes monitoring, especially in hemorrhage and infection (P < 0.05).
ConclusionsThere was no difference among SEEG and subdural cortical electrodes monitoring in surgical results, but SEEG with less hemorrhagic and infectious risks. SEEG is a safe and effective intracranial monitoring method, which can be widely used.
ObjectivesTo review the value of sleep deprivation EEG methodology in the diagnosis of epilepsy.MethodsSuch databases as Pubmed, MEDLINE, The Cochrane Library, Wanfang, VIP and CNKI Data are searched electronically and comprehensively for literature on the diagnosis of epilepsy by sleep deprivation EEG from inception to January 2021. Two reviewers independently screened literature according to the inclusion and exclusion criteria, extracted data, and assessed methodological quality. Then, meta-analysis was performed using Stata software.ResultsA total of 14studies involving 1221 patients were included in total. The results of meta-analysis showed that: Duration of sleep deprivation and effect value of positive rate [ r=0.670, 95%CI (0.664, 0.696), P<0.001 ], duration of the awake period records and effect value of positive rate [ r=0.659, 95%CI (0.596, 0.722), P<0.001 ], duration of sleep period records and effect value of positive rate [ r=0.67, 95%CI(0.619, 0.721), P<0.001 ], with significant differences.ConclusionsThe duration of sleep deprivation, the awake period records, and the sleep period records of sleep deprivation EEG examination, sleep deprivation time between 16 h to 24 h, the awake recording time ≥30 min, and the sleep recording time ≥ 60 min (≤ 3 h) can obviously improve the positive rate of sleep deprivation EEG.
ObjectiveAicardi and Goutières syndrome was first reported as a rare hereditary encephalopathy with white matter involvement in 1984. Typical clinical manifestations include severe mental motor development retardation or regression, pyramidal and extrapyramidal symptoms and signs, epilepsy, microcephaly and frostbite.MethodsTo collect a case of patient who presented with convulsions 14 days after birth without obvious inducement. The child was diagnosed as epilepsy in the local hospital and the symptoms improved after treatment with antiepileptic drugs. At 4 months, the child presented nods and clenched fists, and was diagnosed as infantile spasm. After Adrenocorticotrophic hormone and drug treatment, the symptoms gradually improved. Due to upper respiratory track infection, the child was aggravated at the age of 1 year and 2 months, and then diagnosed as Aicardi-Goutières syndrome by video EEG, skull MRI, fundus and gene screening.ResultsSurgery and treatment with antiepileptic drugs significantly improved the symptoms of the child, and the pathological biopsy of the brain tissue supported the previous diagnosis.ConclusionsThe report of this case will help to improve the clinician's diagnosis and treatment of Aicardi-Goutières syndrome.
Objective To explore the change of EEG waveform recorded by clinical EEG under different filtering parameters. Methods22 abnormal EEG samples of epilepsy patients with abundant abnormal waveforms recorded in Peking University first hospital were selected as the case group (abnormal group), and 30 normal EEG samples of healthy people with matched sex and age were selected as the control group (normal group). Visual examination and power spectrum analysis were then performed to compare the difference of wave forms and spectrum power under different settings of filter parameter between the two groups. ResultsThe results of visual examination show that, lower high-frequency filtering has an effect on the fast wave composition of EEG and may distort and reduce the spike wave. Higher low-frequency filtering has an effect on the overall background and slow wave activity of EEG and may change the amplitude morphology of some slow waves. The results of power spectrum analysis show that, Compare the difference between the EEG normal group and the abnormal group, the main difference under the settings of 0.5~70Hz was on the θ and α3 frequency band, different brain regions were slightly different. In the central region, the difference in the high frequency band (α3, γ1, γ2) decreases or disappears with the decrease of the high frequency filtering. In the rest of the brain, the difference in the δ band appears gradually with the increase of the low frequency filtering. Compare the difference between frontal area and occipital area under different filter set, for the normal group, under the settings of 0.5 ~ 70 Hz, the difference between two regions is mainly on the θ, γ1 and γ2 band. When high frequency filter reduces, the difference between two regions on high frequency band (γ1, γ2) are gradually reduced or disappeared. And when low frequency filter increases, the difference on δ band appears. For the abnormal group, the difference between frontal and occipital region under the settings of 0.5 ~ 70 Hz is mainly on γ1 and γ2 bands. When the high-frequency filter decreases, the difference between two regions on high-frequency bands are gradually decreased or disappeared. All the results can be corrected by FDR. ConclusionThe results show that the filter setting has a significant influence on EEG results. In clinical application, we should strictly set 0.5 ~ 70 Hz bandpass filtering as the standard.
