Construction And Evaluation Of A Nomogram Prediction Model For Germ Infection In Decompensated Patients With Hepatitis C Cirrhosis

ObjectiveElectronic case studies were used to query case data on germ infections in patients with decompensated HCV cirrhosis,and to discovery the affecting factors for germ infections in patients with decompensated hepatitis C cirrhosis.The nomograph prediction model was used to predict and value the risk of germ infections in patients with HCV cirrhosis who could evolve decompensated hepatitis CMethodsA retrospective research was enacted on 574 patients hospitalized for decompensated hepatitis C cirrhosis in the third people’s hospital of Kunming from January 2020 to December 2021,and they were grouped into germ infection organize(163 cases)and non-germ infection organize(411 cases)informed whether germ infection occurred.General patient information,admission complications,and laboratory indicators were used for risk analysis.Through single factor Logistic analysis and LASSO regression,variables were collected,and multivariate logistic regression was used to filtrate the affecting factors.Based on this,a nomograph prediction model was constructed and evaluated.The DCA curve and CIC curve were used to forecast the clinical application worth of the model.ResultsIn this study,28.40%(163/574)of patients developed germ infections,with spontaneous germ peritonitis being 45.03%(86/191)and pulmonary germ infections being 41.36%(79/191);A total of 78 strains of pathogenic bacteria were isolated and cultivated,with Klebsiella pneumoniae 19.23%(15/78)and Escherichia coli 19.23%(15/78)as the main pathogens.Multivariate Logistic regression analysis indicated that age(OR=2.054,95%CI:1.104-3.822,P=0.023),female(OR=1.701,95%CI:1.112-2.602,P=0.014),ascites(OR=2.386,95%CI:1.601-3.557,P<0.001),invasive operation history in the last 2 weeks(OR=2.605,95%CI:1.368-4.960,P=0.004),length of hospital stay≥2weeks(OR=1.629,95%CI:1.098-2.416,P=0.015)were standalone risk factors for germ infection in decompensated patients with hepatitis C cirrhosis.Human blood albumin(OR=0.324,95%CI:0.194-0.542,P<0.001)and total cholesterol(CHOL)(OR=0.675,95%CI:0.549-0.830,P<0.001)were protective factors for germ infection in decompensated patients with hepatitis C cirrhosis.The ROC curve was used to analyze the AUC.The AUC was 0.736.Sensitivity was 80.4%,specificity 65.1%.Hosmer–lemeshow test indicated that the suite of the model had good(χ~~2=9.030,P=0.340).The Bootstrap method was used to verify the data of 574 patients with internal repeated sampling for 1000 times for verification,with an average absolute error of 0.010.The correction curve and ideal curve were basically appropriated,and the forecasted value and actual value were in equal conformity.The decision curve showed that the line graph model had certain clinical practicability in the scope of high risk threshold(0.040～0.715).CIC curve drawn by line graph model could be used for stratified prediction of high risk population.ConclusionThe nomograph model constructed in this study had good predictability,consistency,and clinical practicality,providing a basis for clinicians to initially determine the risk of germ infection in patients with decompensated liver cirrhosis.