Screening Biomarkers and Constructing a Predictive Model for Symptomatic Urinary Tract Infection and Asymptomatic Bacteriuria in Patients Undergoing Cutaneous Ureterostomy: A Metagenomic Next-Generation Sequencing Study

Author:

Yuan Qian12ORCID,Huang Rong12ORCID,Tang Liping12ORCID,Yuan Lijuan3ORCID,Gao Li3ORCID,Liu Yang4ORCID,Cao Ying12ORCID

Affiliation:

1. Department of Nursing, The First Affiliated Hospital of Nanchang University, Nanchang 330006, China

2. Nursing School, Nanchang University, Nanchang 330006, China

3. Genskey Medical Technology Co. Ltd., Beijing 102206, China

4. Department of Clinical Microbiology, The First Affiliated Hospital of Nanchang University, Nanchang 330006, China

Abstract

Objectives. To investigate the clinical diagnostic value of differential flora as biomarkers in patients with symptomatic urinary tract infection (UTI) and asymptomatic bacteriuria (ASB) undergoing cutaneous ureterostomy based on metagenomic next-generation sequencing and construct predictive models to provide a scientific reference for clinical diagnosis and treatment. Material and Methods. According to standard procedures, samples were taken from each patient for routine tests (urine, ureteral stent, and skin swab around the stoma). Cytokine levels in the blood were also detected. Urinary microflora were measured by mNGS, and potential biomarkers for distinguishing UTI and ASB were identified by differential flora. Finally, we generated the predictive models for ASB and UTI using the Lasso method and cytokine levels. Results. Urine culture was performed for 50 patients with cutaneous ureterostomy; 44 of these patients developed bacteriuria. The incidence of symptomatic bacteriuria was 54.55%. Biomarker analysis showed that Propionimicrobium lymphophilum, Staphylococcus haemolyticus, Stenotrophomonas maltophilia, Ralstonia insidiosa, and Aspergillus sydowii all had good predictive performance and were combined in a single model. The predictive model exhibited good prediction performance (area under the curve AUC = 0.8729 , sensitivity = 80 % , specificity = 83.3 % , and cutoff = 1.855 ). We also identified a significant negative correlation between the weight sum of the abundance for these five characteristic pathogens (Sum_weighted_Reads) and levels of the cytokine IL-6 and IL-1β ( P < 0.05 ). Conclusion. mNGS had a higher positive detection rate for pathogens in urine samples. The selected differential bacteria can be used as biomarkers of ASB and UTI, and the prediction model has good predictive performance. Analysis also showed that the occurrence of symptoms was related to individual immunity. Combined with the Sum_weighted_Reads cutoff and cytokine levels (IL-6 and IL-1β) of differential flora, it was possible to judge the severity of symptoms in cutaneous ureterostomy patients with bacteriuria and provide new insights for the treatment and intervention of ASB and UTI.

Funder

Science and Technology Department Foundation of Jiangxi Province

Publisher

Hindawi Limited

Subject

Biochemistry (medical),Clinical Biochemistry,Genetics,Molecular Biology,General Medicine

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