Brief Article
Related factors of urinary tract infections in inpatients based on real world data
Bian Chunhong, Pan Yue, Tan Yanan, Zhang Limin, Wang Rongqi, Zhang Guojun
Published 2022-11-06
Cite as Chin J Prev Med, 2022, 56(11): 1636-1641. DOI: 10.3760/cma.j.cn112150-20220526-00534
Abstract
To analyze the risk factors for urinary tract infection (UTI) among inpatients. The case data of 1 875 inpatients receiving urinary bacterial culture in Beijing Haidian Hospital from October 2019 to May 2021 were analyzed retrospectively. According to the etiological diagnostic criteria of UTI, they were divided into infection group and non-infection group. The species and distribution of pathogens in the infection group were analyzed, and the case data and laboratory indexes were subjected to univariate analysis. The variables with statistical significance were selected for binary logistic regression to analyze the risk factors of urinary tract infection and establish a prediction model. The receiver operating characteristic (ROC) curve was drawn for each parameter included in the model, and the area under the curve (AUC) was calculated. The diagnostic and predictive efficacy of each parameter alone and their combination for UTI were evaluated. So, a total of 1 162 patients with non-infection group and 713 patients with UTI were detected. Among the cultured pathogens, the constituent ratio of Gram-negative bacteria, Gram-positive bacteria and fungi was 57.2%(408/713), 35.9%(256/713) and 6.9%(49/713) respectively. Multivariate analysis showed that, Age, duration of urinary catheterization>7 d, stroke and orthopedic surgery were the risk factors of UTI among inpatients. The use of antibiotics is a protective factor for urinary tract infections. The prediction model of UTI was established by the risk factors, age, duration of urinary catheterization>7 d, stroke, orthopedic surgery, urinary leukocyte esterase, urinary nitrite and Coefficient of variability of red blood cell volume distribution width (RDW-CV). The AUC of the combination of the eight parameters in diagnosing and predicting UTI was 0.835 (95%CI: 0.816-0.855), with the sensitivity of 70.7% and the specificity of 82.8%. In conclusion,the combination of the eight parameters can better assist in the diagnosis and prediction of UTI, and provide an experimental basis for clinicians to judge UTI.
Key words:
Urinary tract infections; Pathogens; Risk factors; Logistic regression model
Contributor Information
Bian Chunhong
Laboratory Diagnosis Center,Beijing Tiantan Hospital Affiliated to Capital Medical University, Beijing 100070,China
Clinical Laboratory, Beijing Haidian Hospital,Beijing 100089,China
Pan Yue
Clinical Laboratory, Beijing Haidian Hospital,Beijing 100089,China
Tan Yanan
Clinical Laboratory, Beijing Haidian Hospital,Beijing 100089,China
Zhang Limin
Laboratory Diagnosis Center,Beijing Tiantan Hospital Affiliated to Capital Medical University, Beijing 100070,China
Wang Rongqi
Clinical Laboratory, Beijing Haidian Hospital,Beijing 100089,China
Zhang Guojun
Laboratory Diagnosis Center,Beijing Tiantan Hospital Affiliated to Capital Medical University, Beijing 100070,China
Beijing Engineering Research Center of Immunological Reagents Clinical Research,Beijing 100070,China
Key Laboratory for Quality Control of In Vitro Diagnostics, National Medical Products Administration, Beijing 100070,China
