Clinical risk scoring system for predicting extended-spectrum β-lactamase-producing Escherichia coli infection in hospitalized patients

Abstract

Extended spectrum β-lactamase-producing Escherichia coli (ESBL-EC) has important implications for infection control and empiric antibiotic prescribing. This study aims to develop a risk scoring system for predicting ESBL-EC infection based on local epidemiology. The study retrospectively collected eligible patients with a positive culture for E.coli during 2011 to 2014. The risk scoring system was developed using variables independently associated with ESBL-EC infection through logistic regression-based prediction. Area under the receiver-operator characteristic curve (AuROC) was determined to confirm the prediction power of the model. Predictors for ESBL-EC infection were male gender [odds ratio (OR): 1.53],age ≥55 years (OR: 1.50), healthcare-associated infection (OR: 3.21), hospital-acquired infection (OR: 2.28), sepsis (OR: 1.79), prolonged hospitalization (OR: 1.88), history of ESBL infection within one year (OR: 7.88), prior use of broad-spectrum cephalosporins within three months (OR: 12.92), and prior use of other antibiotics within three months (OR: 2.14). Points scored ranged from 0 to 47, and were divided into three groups based on diagnostic performance parameters: low risk (score: 0-8; 44.57%), moderate risk (score:9-11; 21.85%) and high risk (score: ≥12; 33.58%). The model displayed moderate power of prediction (AuROC: 0.773; 95% confidence interval: 0.742-0.805) and good calibration (Hosmer-Lemeshow χ(2)=13.29; P=0.065). This tool may optimize the prescribing of empirical antibiotic therapy, minimize time to identify patients, and prevent spreading of ESBL-EC. Prior to adoption into routine clinical practice, further validation study of the tool is needed.