Background: 2019 Novel coronavirus disease (COVID-19) is turning into a pandemic globally lately. There were few reports illustrated the expression of Angiotensin II (AngII) in COVID-19. This study aimed to demonstrate the expression of AngII in COVID-19 and how it correlated to the disease.Methods and Results: We enrolled 55 patients with COVID-19 admitted to Renmin Hospital of Wuhan University from January 21st to February 21st, 2020. Demographic data were collected upon admission. COVID-19 nuclear acid, plasma AngII, Renin and aldosterone in the lying position without sodium restriction, and other laboratory indicators were together measured by the laboratory department of our hospital. Of the 55 patients with COVID-19, 34(61.8%) had an increased level of AngII. The severity of COVID-19 and male is positively related with the level of AngII. The level of blood lymphocyte, PCT, ALT, and AST were remarkably severe with those of normal level of AngII (P < 0.05). CD4/CD8 cells ratio was significantly higher than those of normal level of AngII (P < 0.05). The results of binary logistic regression analysis showed that the severity of COVID-19 (OR=4.123) and CD4/CD8 ratio(OR=4.050) were the co-directional impact factor while female(OR=0.146) was inverse impact factor of elevated AngII level.Conclusion: High rate of increased level of AngII and its gender differences were detected in COVID-19 patients. Elevated AngII level were correlated with the severity of COVID-19 and CD4/CD8 ratio.
Background: NeurologicalEarly prediction model for seizures in influenza complications of influenza are associated with high morbidity and mortality in children. The prognosis could be improved if early treatments are undertaken. Objective: To establish and validate an early prediction model to discriminate among neurological complications such as seizures, acute influenza virus-associated encephalitis (IAE), and acute necrotizing encephalopathy (ANE) in children with influenza. Methods: This was a retrospective single-center case-control study conducted at the Guangzhou Women and Children's Medical Center in Guangzhou (GWCMC), China, from November 2012 to January 2020. The random forest model was used to screen the characteristics and construct an early prediction model for convulsions, IAE, and ANE. Results: Of the 433 patients (294 male, 139 female; median age 2.8 (1.7,4.8) years), 278 (64.2%) had seizures, 106 (24.5%) had IAE, and 49 (11.3%) had ANE; 348 patients were in the training set and 85 in the validation set. When 10 variables were included, the cross-validation error was minimal; convulsions, procalcitonin, urea, γ-glutamyltransferase, aspartate aminotransferase, albumin/globulin ratio, α-hydroxybutyric dehydrogenase, alanine aminotransferase, alkaline phosphatase, and C-reactive protein were included. The likelihood of having only seizures decreased with increasing procalcitonin, urea, γ-glutamyltransferase, α-hydroxybutyric dehydrogenase, alanine aminotransferase, and aspartate aminotransferase, and with decreasing albumin/globulin ratio and alkaline phosphatase. The prediction model gave a prediction accuracy of 84.2%. Conclusion: This model can distinguish the seizures from IAE and from ANE. This could allow for the early management of children with influenza in order to prevent morbidity and mortality. The biochemical/hematologic markers lacked specificity.
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