Analysis of factors of pulmonary fungal infection in mice in respiratory medicine department based on logistic regression analysis model and Progranulin

摘要

The objective of this research is to solve the current medical problems of a high incidence of fungal infections in the lungs, high misdiagnosis rate, and high mortality. In this study, firstly, the logistic regression model was used to conduct. Risk factors of pulmonary fungal infection in respiratory department were analyzed. Then a model of pulmonary fungal infection in mice was constructed, and the expression difference of Progranulin (PGRN) in serum was detected by enzyme-linked immuno sorbent assay (ELISA). The expression of PGRN in lung tissues of mice infected by pulmonary fungi was detected by Western bolt method and quantitative polymerase chain reaction (PCR). The PGRN protein and mRNA expression in the lung epithelial cells of mice were detected after the infection. Results logistic regression model was used to analyze the main risk factors affecting pulmonary infection in mice. The risk factors of pulmonary fungal infection were indent catheter, hypoproteinemia, long-term use of glucocorticoid and long-term use of antibiotics. The PGRN content in serum was obviously higher than that before pulmonary fungal infection (P