ObjectiveTo analyze the clinical features of psychogenic non-epileptic seizures (Psychogenic nonepileptic seizures, PNES) in Tibetan population in Tibet, so as to help clinicians identify the disease.MethodsRetrospective analyzed the clinical data of patients with PNES in the Department of Neurology, People's Hospital of Tibet Autonomous Region from June 2016 to December 2018.ResultsIn general clinical data, there were significant differences between male and female patients in the results of video electroencephalogram (EEG) monitoring the non-epileptic seizures (P< 0.05). There were no significant differences in mean age, mean onset time, family history of epilepsy, head injury and marital status between male and female patients (P> 0.05). There was no significant difference in symptoms between male and female, but there were differences among different age groups (P> 0.05). In the onset age, the main manifestation was young women, but there was no significant difference in the onset of PNES among different age groups.ConclusionsThere was significant differences between male and female PNES petients, but no significant differences in onset time, marriage and family history of epilepsy between the male and female patients with PNES in Tibet. The clinical manifestations of PNES were different in different ages of patients in Tibet.
ObjectiveThe purpose of the research is to study the distribution and early warning of electroencephalogram (EEG) in acute mountain sickness (AMS). MethodsA total of 280 healthy young men were recruited from September 2016 to October 2016. The basic data were collected by the centralized flow method, the general situation of the division of the investigators after the training, the Lewis Lake score, the computer self-rating anxiety scale and depression scale, and the collection of EEG. Follow up in three months. Results94 of the patients with AMS, morbidity is 33%, 21 (22.34%) of the patients are moderate to severe, 73 (77.66%) are mild, morbidity is 26.67%. The abnormal detection rate of electrogram was 7.9% (22/280), which were mild EEG, normal EEG abnormal rate was 8.6% (16/186), abnormal detection rate of mild AMS was 4.1% (3/73), and the abnormal detection rate was 14.3% (3/21) in the medium / heavy AMS. The latter was significantly different from the previous (P < 0.05). Three months follow-up of this group of patients with 0 case of high altitude disease. Conclusions The EEG in AMS is mainly a rhythm irregular, unstable, poor amplitude modulation; or two hemisphere volatility difference of more than 50% or slightly increased activity. The result is statistically significant, suggesting that EEG distributions has possible early warning of AMS.