1.Correlation between cerebral glucose metabolism and all sorts of paediatric epilepsy or seizure frequency
Qiongxiang ZHAI ; Huiling YANG ; Suzhen CAO ; Jian DING ; Huixian QIAO ; Yunbao PAN
Chinese Journal of Pathophysiology 2000;0(08):-
AIM:To investigate the correlation between cerebral glucose metabolism and paediatric epilepsy or seizure type and seizure frequency.METHODS:To observe the cerebral glucose metabolism in epileptogenic focus,18F-FDG positron emission computed tomography(PET) brain imaging tests were carried out in 86 cases of paediatric epilepsy diagnosed by EEG and MRI.RESULTS:Compared to control group,significantly statistical differences between children epilepsy group and control group in PET brain imaging were observed(P0.05) was observed.CONCLUSION:Cerebral glucose metabolism of paediatric epilepsy is abnormal.The abnormal PET with varieties of epilepsy is found in different brain district.There is positive correlation between the abnormal intensity of PET imaging and the severity or seizure frequency of epilepsy.
2.Expression characteristic of autoantibodies and association with outcome in COVID-19 patients
Bokun ZHENG ; Yueting TANG ; Gui YANG ; Yunbao PAN ; Yirong LI
Chinese Journal of Laboratory Medicine 2022;45(12):1259-1266
Objective:To investigate the difference and characteristics of autoantibodies expression in patients infected by 2019-nCoV with various severity, and explore the associations between expression profile of autoantibodies and prognosis of COVID-19 patients.Methods:This retrospective study was conducted on patients with COVID-19 admitted to Zhongnan Hospital, Wuhan University from January 30, 2020 to March 16, 2020. Data on medical records, expression of autoantibodies including antinuclear antibody profile (ANA), anticardiolipin antibody (ACA), inflammatory factor and other laboratory indexes were collected and analyzed. The age and sex matched disease controls (cases of pulmonary infection unrelated to 2019-nCoV infection and autoimmune disease) and healthy controls (healthy check-up individuals) were also included. Following groups were established, ANA test groups: 72 cases of COVID-19 group (including 17 critical and severe cases, and 55 mild cases), 37 disease controls and 44 healthy controls; ACA test groups: 111 cases of COVID-19 group (including 37 critical and severe cases, and 74 mild cases), 37 disease controls and 40 healthy controls. The difference of positive rate or expression level of autoantibodies among various groups was analyzed, and the difference of inflammatory biomarkers and other parameters were compared between patients with ANA positive results and negative results. The Spearman correlation test was applied to determine the relationship between ACA and other parameters. Kaplan-Meier estimation was used to plot survival curves, the log-rank analysis was utilized to explore the association between antibodies and outcome of COVID-19 patients.Results:The positive rate of antibodies was significantly higher in the COVID-19 group than disease and healthy control groups, the ANA fluorescence: 22.22% (16/72), 5.41% (2/37), 6.82% (3/44); ANA spectrum:26.39% (19/72), 8.11% (3/37), 9.09% (4/44); and ACA:37.84% (42/111), 8.11% (3/37), 5.00% (2/40); all P<0.05. The positive rate of ANA, ACA-IgM and the expression level of ACA-IgM were significantly higher in severe COVID-19 subgroups (critically and severe COVID-19 patients) than in the mild COVID-19 patients (the ANA fluorescence: 47.06% [8/17] vs. 14.55% [8/55], ANA spectrum:66.67% [9/17] vs. 18.18% [10/55], ACA-IgM:30.43% [10/37] vs. 9.46% [7/74]; all P<0.05). There were significant differences in the number of red blood cells, hemoglobin concentration, hematocrit, activated partial thromboplastin time, C-reactive protein, interleukin-6 and serum amyloid A between COVID-19 ANA-positive group and COVID-19 ANA-negative group (all P<0.05). The level of ACA-IgM was positively correlated with white blood cell count ( r=0.354, P<0.001), neutrophil count ( r=0.344, P<0.001), platelet count ( r=0.198, P=0.038), D-Dimer ( r=0.260, P=0.009), glutamic-pyruvic transaminase ( r=0.214, P=0.024), γ-glutamyl transpeptidase ( r=0.283, P=0.003), blood urea nitrogen ( r=0.223, P=0.019), and negatively correlated with superoxide dismutase ( r=-0.228, P=0.020). Survival analysis showed that cumulative survival rate of event-free survival (EFS) was lower in patients with positive ANA/ACA-IgM results than in patients with negative ANA/ACA-IgM results ( P<0.05). Conclusions:ANA and ACA autoantibodies can be detected in COVID-19 patients. The positive rate and the expression level of ANA and ACA increase in proportion with the severity of COVID-19 patients. ANA and ACA-IgM could be used as risk stratification determinants for predicting survival of COVID-19 patients.