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Author Yu, Yuetian ♦ Shen, Hui ♦ Zhu, Cheng ♦ Guo, Ruru ♦ Gao, Yuan ♦ Lu, Liangjing
Editor Reich, Adam
Source Hindawi
Content type Text
Publisher Hindawi
File Format PDF
Copyright Year ©2018
Language English
Abstract Objective. To investigate the prevalence and risk factors of infections caused by Extended-Spectrum β-Lactamase (ESBL) producing Escherichia coli (E. coli) in systemic lupus erythematosus (SLE) patients and develop a predictive model. Methods. Three hundred and eighty-four consecutive SLE patients with E. coli infection were enrolled in this retrospective case control study from January 2012 to December 2017. Prevalence and antimicrobial susceptibility pattern of ESBL producing E. coli were analyzed. Multivariate analysis was performed to determine the risk factors. Sensitivity and specificity were obtained at various point cutoffs and area under the receiver operator characteristic curve (AuROC) was determined to confirm the prediction power of the model. Results. Of the total 384 E. coli strains tested, 212 (55.2%) produced ESBL. The majority of these isolates were from urine (44.3%). Carbapenems (>80%) and amikacin (89.6%) had good activity against ESBL producing E. coli. Eleven variables were identified as independent risk factors for ESBL producing E. coli infection including Enterobacteriaceae colonization or infection in preceding year (OR=8.15, 95%CI 5.12–21.71), daily prednisone dose > 30mg (OR=5.48, 95%CI 3.12–13.72), low C3 levels (OR=2.17, 95%CI 1.62–6.71), nosocomial acquired infection (OR=4.12, 95%CI 1.98–8.85), etc. The model developed to predict ESBL producing E. coli infection was effective, with the AuROC of 0.840 (95% CI 0.799-0.876). Conclusions. The prevalence of ESBL producing E. coli was increasing with high antibiotics resistance in patients with SLE. The model revealed excellent predictive performance and exhibited a good discrimination.
ISSN 23146133
Learning Resource Type Article
Publisher Date 2018-11-18
Rights License This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
e-ISSN 23146141
Journal BioMed Research International
Volume Number 2018
Page Count 9


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