Correlation Analysis Of Influenza A Virus Infection With Invasive Pulmonary Mycosis And Establishment Of Regression Prediction Model

BackgroundInvasion pulmonary mycosis?IPM?refers to diseases caused by acute and chronic histopathological damage caused by fungi directly invading the lungs or bronchi.Common in immunodeficiency,previous immunosuppressive therapy,physical or hematologic malignancies after chemotherapy and solid organ transplant recipients.However,Shah MM[2]and other scholars found that influenza patients with normal immune function in the past will also be infected with invasive pulmonary aspergillosis?IPA?,which indicates that influenza patients suffer from invasive pulmonary fungus.The risk of illness is higher.According to research,about29%of influenza patients will have bacterial infections,followed by toxic pneumonia and acute respiratory distress syndrome,which are the leading causes of death in influenza patients[3-5].Vanderbeke L and other scholars[6]have shown that since2009,the number of cases of influenza and invasive pulmonary fungal disease and literature review have increased significantly.Due to the high mortality rate of invasive pulmonary fungal disease,data on influenza A virus infection combined with invasive pulmonary fungal disease are limited in this case.Therefore,the analysis of the clinical characteristics of influenza A virus infection combined with invasive pulmonary fungal disease and related risk factors can not only guide clinical diagnosis and treatment,but also prevent the occurrence of fungal infection,reduce its morbidity and mortality,and have important clinical significance.ObjectiveTo explore the related factors of influenza a virus infection complicated with invasive pulmonary mycosis,a Logistic regression prediction model was established accordingly,and to evaluate the value of this model in predicting influenza a virus infection complicated with IPM,so as to improve the reference for clinical diagnosis and treatment.Research methodsThis study selected a retrospective analysis of 179 confirmed cases of influenza A virus infection in the First Affiliated Hospital of Zhengzhou University from November 2017 to March 2019,including 121 males and 58 females with an average age of 50.28.±20.10 years old.Exclude patients with previously diagnosed invasive fungal disease and chronic pulmonary aspergillosis.The diagnosis of influenza A virus infection is based on the influenza diagnosis and treatment program?2018edition?.The diagnosis of IPM is based on the consensus of the Chinese Medical Association's diagnosis and treatment of pulmonary fungal diseases.It is divided into influenza A combined with IPM group and influenza A non-merged.IPM group.The general conditions,clinical symptoms,laboratory findings and chest CT of the two groups were compared.According to the results of single factor analysis,the statistically significant variables were included in the binary logistic regression analysis.Logistic predictive regression models were established based on the analysis results.The working curve of the worker detects the diagnostic value of the predictive regression model.Results1.The incidence of influenza A virus infection combined with invasive pulmonary fungal disease was 23.5%,including 42 cases of influenza A virus infection combined with invasive pulmonary fungal disease,including 35 fungi,including 13 cases of Candida albicans?37.1%?There were 12 cases?34.3%?of Aspergillus fumigatus,6 cases?17.1%?of Aspergillus flavus,2 cases?5.7%?of Candida tropicalis,1 case?2.9%?of Candida krusei,and 1 case?2.9%?of Penicillium.2.Univariate analysis showed that patients were diagnosed with diabetes,solid organ transplant recipients,cerebrovascular disease,hypertension,dyspnea,positive serum G test,positive serum GM test,glycosylated hemoglobin>7.0,exudation,consolidation and cavities,etc.11 One factor was associated with the infection of influenza A virus combined with IPM,the difference was statistically significant?P<0.10?,but because of the interaction between variable diabetes and variable glycosylated hemoglobin>7.0,we only included glycosylated hemoglobin>7.0 into Logistic.Regression analysis,so the above 10 factors were included as independent variables in binary logistic regression analysis.3.Binary logistic regression analysis showed:cerebrovascular disease?OR:0.270,OR?95%CI?:1.026-1.671?,serum G test positive?OR:1.103,OR?95%CI?:1.058-1.150?,serum GM test positive?OR:1.180,OR?95%CI?:1.089-1.278?,glycated hemoglobin>7.0?OR:1.063,OR?95%CI?:1.028-1.099?,exudation?OR:1.223,OR?95%CI?:1.074-1.393?is an independent risk factor for the infection of influenza A virus with invasive pulmonary fungal disease.Based on this,the logistic regression equation Logistic?P?=-7.227+0.270X₁+0.105X₂+0.177X₃+0.066X₄+0.216X₅ was established.4.The area under the ROC curve of the Logistic regression prediction model is0.939.The diagnostic sensitivity,specificity,positive predictive value and negative predictive value are 83.33%,95.62%,85.37%,and 94.92%,respectively.The area under the ROC curve is larger than the serum alone.The AUC of the G test and the GM test.Conclusions1.The incidence of influenza A virus infection combined with invasive pulmonary fungal disease is 23.5%,which is consistent with many foreign scholars.2.For patients diagnosed with influenza A virus infection,there are cerebrovascular disease,glycosylated hemoglobin>7.0,serum G test positive,serum GM test positive,early chest CT suggesting osmotic changes can be used as an independent risk to predict the onset of invasive pulmonary fungal disease factor.The sensitivity and specificity of the predictive models based on the above risk factors were 83.33%and 95.62%,respectively.This logistic regression model can better predict the probability of IPM in patients infected with influenza A virus.