Objectives To analyze the prevalence and clinical features of depression, anxiety, depression and anxiety in Tibetan patients with epilepsy and to improve the diagnosis and treatment. Methods 102 patients with epilepsy, who had been admitted to the Department of Neurology of the People's Hospital of Tibet Autonomous Region from January 2017 to December 2017, were diagnosed according to the Chinese Standard Classification and Diagnostic Criteria for Mental Disorders (3rd Edition) (CCMD-3). The Hamilton depression scale (HAMD 24 items) and the Hamilton anxiety scale (HAMA 14 items) were used to measure depression and anxiety. Different genders, ages, durations, frequency of attacks, and seizures types were analyzed for depression, anxiety, depression and anxiety. Univariate analysis was used to screen the factors that may cause depression, anxiety, depression and anxiety in patients with epilepsy. Logistic regression was used to analyze the risk factors of depression, anxiety, depression and anxiety in patients with epilepsy. Results Among the 102 patients with epilepsy, 35 (34.31%) comorbid depression, 10 (9.80%) comorbid anxiety, and 54 (52.94%) comorbid depression and anxiety. Univariate analysis showed that there was a significantly statistical difference in the duration of the disease and the frequency of seizures in local patients with epilepsy (P<0.05). There was a statistically significant difference in the frequency of epileptic seizures and anxiety (P<0.05). Multivariate logistic regression analysis showed that the probability of anxiety in patients with a disease duration of ≤2 years was only 10.1% of those with a course >2 years [OR=0.101, 95%CI (0.012, 0.915), P<0.05]; and the frequency of seizures was not an risk factors for epileptic comorbid with anxiety (P>0.05). The rate of depression and anxiety in patients with seizure frequency >2 times per month was 4.853 times higher than that of patients with seizure frequency ≤2 times per month [OR=4.853, 95%CI (2.024, 11.634), P<0.05]. Conclusions Tibetan patients with epilepsy have a high prevalence of depression, anxiety, depression and anxiety. In the diagnosis and treatment, we should strengthen the understanding and provide the appropriate prevention and treatment to improve the diagnosis and treatment level.
ObjectiveTo analyze the types and characteristics of common paroxysmal diseases in order to improve the diagnosis of onset types and to analyze the related factors of epileptic seizures in Tibetan population.Methods510 patients with paroxysmal diseases were enrolled in the Department of Neurology, People's Hospital of Tibet Autonomous Region from June 2013 to December 2018 and the video electroencephalogram (VEEG) data were analyzed.ResultsAmong the 510 patients, there were 35 types of paroxysmal diseases, 335 cases (65.69%) of seizures and 86 cases (16.86%) of psychogenic non-epileptic seizures (PNES). There were significant differences in the incidence of seizures between male and female patients (P<0.05), the incidence of seizures were different at different altitude and the concentration of hemoglobin (P<0.05), the course of seizures was always more than 2 years (P<0.05), and the frequency and age of seizures were higher, but there were no significant difference, and epileptic patients in Tibet were more likely to be young adults (34.51%).ConclusionsThere are many kinds of paroxysmal diseases in Tibetan population, and epileptic seizures are the main type. There was a qualitative relationship between the incidence of epilepsy and altitude. The incidence of epilepsy didn’t increase along with the increase of hemoglobin, and the course of seizures was mostly more than 2 years.
Objectives Retrospective analysis of the Tibetan convulsive status epilepticus (CSE) for the aetiology, prognosis and its influencing factors in Tibet area. Methods Through electronic patient record, making “epilepsy”, “status epilepticus ”, “epileptic seizure” as keywords, convulsive status epilepticus patients in the People’s Hospital of Tibet Autonomous Region hospitalized from January 2015 to December 2020 were retrospectively observed, gathering their clinical data and aided examinations furthermore, and the prognoses were returned by telephone, meanwhile the functional status of those patients was assessed by the modified rankin scale. and the causes differ in gender, age, out-of-hospital antiepileptic treatment, family history of epilepsy and history of epilepsy were analyzed. The prognostic factors were analyzed by logistic regression. Results A total of 2 254 hospitalized patients with epilepsy were retrieved, including 331 CSE patients aged 14~84 years, 219 males and 112 females. There were 36 lost calls, 62 CSE deaths (21.01%), and 4 adverse outcomes (non-death)(1.7%).There were statistically significant differences in etiology of CSE in different ages and history of epilepsy (P<0.05), but there were no statistically significant differences in gender, out-of-hospital antiepileptic treatment, progression of refractory status epilepticus and family history of epilepsy. Cerebrovascular disease was the main cause of CSE in people aged 45 and over (54 cases), while the main cause of CSE in people aged under 45 was unknown (104 cases).Among the patients with previous history of epilepsy, the highest proportion was unknown cause [117 cases (48.8%)]; Among patients without a history of epilepsy, cerebrovascular disease [34 cases (37.4)] was the most common cause of CSE. Multivariate logistic regression analysis of prognostic factors of CSE showed that gender, age, GCS and electrolyte disorder had statistically significant effects on the death of CSE patients (P<0.05), while altitude and their duration and other factors had no statistically significant effects on the death of CSE patients (P>0.05). ConclusionsCerebrovascular disease is the leading cause of CSE in people aged 45 and over. Male, advanced age, low GCS score at discharge, and electrolyte disorder were risk factors.
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.