Construction of a diagnostic model for ulcerative colitis with Clostridioides difficile infection based on intestinal flora and metabolomics
WANG Zhuo
WAN Jian
ZHANG Yujie
HE Wenfang
WU Kaichun
Abstract:Objective To establish a diagnostic model for the presence of Clostridioides difficile(CD)infection in patients with ulcerative colitis(UC)based on clinical data,microorganisms and microbial metabolites.Methods Fifty-eight UC patients in Xijing Hospital,Air Force Medical University from 2018 to 2019 were included in this study and divided into UC group without CD infection(n =29)and UC group with CD infection(n =29).The differences in clinical data,flora and metabolites between the two groups were compared,and logistic regression analysis was used to establish a diagnostic model for the presence of CD infection in UC patients.The efficacy of the diagnostic model was evaluated by area under the receiver operating characteristic curve(AUC)and goodness-of-fit test.Results The results of univariate analysis showed that the fecal microbial metabolites hexadecane,lactic acid,coniferyl alcohol,3-phenyllactic acid,C-reactive protein,and Clostridium Ⅺ were associated with CD infection in UC patients(P<0.05),and the results of multivariate analysis showed that hexadecane,lactic acid,and Clostridium Ⅺ were independent predictors of the presence of CD infection in UC patients.A logistic regression model was established with 3 factors:logit(P)=0.724-0.980×hexadecane +1.512×lactic acid + 1.298×Clostridium Ⅺ.The AUC of this model was 0.873(95%CI:0.782-0.964),and the diagnostic threshold of this model was0.411 at the maximum of the Youden's index(0.655),with a sensitivity of 79.3%and a specificity of 86.2%.In Hosmer-Lemeshow test,x2 =5.381 and P was 0.716.Conclusion The clinical diagnostic model of CD infection in UC patients based on intestinal microorganisms and microbial metabolites has good efficacy and can provide reference for further clinical decision-making.
Keywords:ulcerative colitisClostridioides difficilegut microbiotametabolitediagnostic model
Publication Date:2024-03-28
Online Publishing Date:2026-08-26(First online date of this platform, not the publication date of the document)
Pages:5( 332-336 )
Journal of Air Force Medical University

Journal of Air Force Medical University

AMI
ISSN:2097-1656
Year, Vol.(Issue):2024,(3)