ABSTRACT
Objective:To explore the differences in laboratory indicators test results of coronavirus disease 2019 (COVID-19) and influenza A and to establish a differential diagnosis model for the two diseases, and to clarify the clinical significance of the model for distinguishing the two diseases. Methods :A total of 56 common COVID-19 patients and 54 influenza A patients were enrolled , and 24 common COVID-19 patients and 30 influenza A patients were used for model validation. The average values of the laboratory indicators of the patients 5 d after admission were calculated,and the elastic network model and the stepwise Logistic regression model were used to screen the indicators for identifying COVID-19 and influenza A. Elastic network models were used for the first round of selection,in which the optimal cutoff of lambda was chosen by performing 10-fold cross validations. With different random seeds,the elastic net models were fit for 200 times to select the high-frequency indexes ( frequency>90% ). A Logistic regression model with AIC as the selection criterions was used in the second round of screening uses;a nomogram was used to represent the final model;an independent data were used as an external validation set,and the area under the curve (AUC) of the validation set were calculate to evaluate the predictive the performance of the model. Results:After the first round of screening, 16 laboratory indicators were selected as the high-frequency indicators. After the second round of screening,albumin/ globulin (A/G),total bilirubin (TBIL) and erythrocyte volume (HCT) were identified as the final indicators. The model had good predictive performance , and the AUC of the verification set was 0. 844 (95% CI:0. 747-0. 941). Conclusion:A differential diagnosis model for COVID-19 and influenza A based on laboratory indicators is successfully established,and it will help clinical and timely diagnosis of both diseases.Copyright © 2022 Jilin University Press. All rights reserved.
ABSTRACT
In recent years, members of the Coronaviridae family have caused outbreaks of respiratory diseases (MERS, SARS, and COVID-19). At the same time, the potential of radiation-induced inactivation of this group of viruses have been little studied, although radiation technologies can be widely used both in the processing of personal protective equipment and in the sterilization of vaccines. In the present work, the effect of 10 MeV electron beams and 7.6 MeV bremsstrahlung on the coronavirus infection pathogen (transmissible gastroenteritis virus) has been studied in vitro. In the given experimental conditions, irradiation with photons turned out to be more effective. The virus-containing suspension frozen at -86°C was the most resistant to radiation: the dose required for complete inactivation of the virus in this case was from 15 kGy, while for the liquid suspension and lyophilized form the sterilizing dose was from 10 kGy. At lower radiation doses for all samples during passaging in cell culture, residual infectious activity of the virus was observed. These differences in the efficiency of inactivation of liquid and frozen virus-containing samples indicate a significant contribution of the direct effect of radiation.