Epidemiology, risk factors, and prediction score of carbapenem resistance among inpatients colonized or infected with 3rd generation cephalosporin resistant Enterobacterales
Authors: Moghnieh Rima , Abdallah Dania , Jadayel Marwa , Zorkot Wael , El Masri Hassan , Dib Marie Joe , Omar Tasnim , Sinno Loubna , Lakkis Rawad , Jisr Tamima 
Published: July 2021

AbstractIn this study, we determined the incidence and risk factors of Carbapenem-resistant Enterobacterales (CRE) acquisition in inpatients with 3rd generation cephalosporin-resistant (3GCR) Enterobacterales at a tertiary-care hospital in Lebanon, and suggested a risk prediction score for it. This is a retrospective matched case–control study of inpatients with 3GCR Enterobacterales that are carbapenem resistant (cases) versus those with carbapenem-sensitive isolates (controls). Data analysis was performed on IBM SPSS program, version 23.0 (Armonk, NY, USA: IBM Corp.). Categorical variables were compared between cases and controls through bivariate analysis and those with statistical significance (P < 0.05) were included in the forward stepwise multiple logistic regression analysis. To develop the CRE acquisition risk score, variables that maintained statistical significance in the multivariate model were assigned a point value corresponding to the odds ratio (OR) divided by the smallest OR identified in the regression model, and the resulting quotient was multiplied by two and rounded to the nearest whole number. Summation of the points generated by the calculated risk factors resulted in a quantitative score that was assigned to each patient in the database. Predictive performance was determined by assessing discrimination and calibration. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated for different cutoffs of the score. The incidence of CRE acquisition significantly increased with time from 0.21 cases/1000 patient-days (PD) in 2015 to 1.89 cases/1000PD in 2019 (r2 = 0.789, P = 0.041). Multivariate analysis of matched data revealed that the history of cerebrovascular disease (OR 1.96; 95% CI 1.04–3.70; P = 0.039), hematopoietic cells transplantation (OR 7.75; 95% CI 1.52–39.36; P = 0.014), presence of a chronic wound (OR 3.38; 95% CI 1.73–6.50; P < 0.001), endoscopy done during the 3 months preceding the index hospitalization (OR 2.96; 95% CI 1.51–4.73; P = 0.01), nosocomial site of acquisition of the organism in question (OR 2.68; 95% CI 1.51–4.73; P = 0.001), and the prior use of meropenem within 3 months of CRE acquisition (OR 5.70; 95% CI 2.61–12.43; P < 0.001) were independent risk factors for CRE acquisition. A risk score ranging from 0 to 25 was developed based on these independent variables. At a cut-off of ≥ 5 points, the model exhibited a sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 64.5%, 85.8%, 82%, 70.7% and 75%, respectively. We also showed that only meropenem consumption intensity and CRE acquisition incidence density showed a strong positive correlation(r = 0.798, P = 0.106), unlike imipenem (r = − 0.868, P = 0.056) and ertapenem (r = 0.385, P = 0.522). Patients with a score of ≥ 5 points in our model were likely to acquire CRE. Only meropenem was associated with CRE carriage. Our proposed risk prediction score would help target surveillance screening for CRE amongst inpatients at the time of hospital admission and properly guide clinicians on using anti-CRE therapy.