AUTHOR=Jiang Shengming , Wei Yangyan , Ke Hu , Song Chao , Liao Wenbiao , Meng Lingchao , Sun Chang , Zhou Jiawei , Wang Chuan , Su Xiaozhe , Dong Caitao , Xiong Yunhe , Yang Sixing 

TITLE=Building a nomogram plot based on the nanopore targeted sequencing for predicting urinary tract pathogens and differentiating from colonizing bacteria

JOURNAL=Frontiers in Cellular and Infection Microbiology

VOLUME=Volume 13 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/cellular-and-infection-microbiology/articles/10.3389/fcimb.2023.1142426

DOI=10.3389/fcimb.2023.1142426

ISSN=2235-2988

ABSTRACT=Background: The identification of uropathogens and urinary tract colonizers conduces to guide the antimicrobial therapy to reduce resistant bacterial strains and study urinary microbiota. This study established a nomogram based on the nanopore targeted sequencing (NTS) and other infectious risk factors to distinguish uropathogens from colonizers. 
Methods: Basic information, medical history and multiple urine test results were continuously collected and analyzed by LASSO regression, and multivariate logistic regression was used to determine the independent predictors and construct nomogram. Using receiver operation characteristics, area under curve, decision curve analysis and calibration curves evaluated the performance of nomogram. 
Results: In this study, the detection rate of uropathogens in patients with suspected urinary tract infections was 74.12% (401/541). Regression analysis showed that the logarithmic form of reads number (ln(reads)) and the number of microbial species in urinary tract of NTS, urine cultures, age, urologic neoplasms, glycosuria and nitrite were independently associated with uropathogens. The nomogram was constructed using predictor variables above. The ln(reads) contributed to the identification of uropathogens (AUC=0.668) with corresponding cutoff values being 7.042, and the performance of nomogram with ln(reads) (AUC = 0.767, 95% CI 0.726–0.807) was significantly better (Z = 2.304, p-value = 0.021) than that without ln(reads) (AUC = 0.727, 95% CI 0.681–0.772). 
Conclusions: The nomogram with ln(reads) helps to identify uropathogenic bacteria from colonized bacteria in patients suspected urinary tract infections. NTS has shown great potential in etiological detection and can significantly increase the value of the nomogram to differentiate uropathogens from colonizers.