• J Emerg Med · Jul 2023

    Observational Study

    PREDICTION OF MULTIDRUG-RESISTANT BACTERIA IN URINARY TRACT INFECTIONS IN THE EMERGENCY DEPARTMENT.

    • Jesus Ruiz-Ramos, Álvaro Eloy Monje-López, David Medina-Catalan, Sergio Herrera-Mateo, Hector Hernández-Ontiveros, María Alba Rivera-Martínez, Celso Soares Pereira-Batista, and Mireia Puig-Campmany.
    • Pharmacy Department, Hospital Santa Creu i Sant Pau, Barcelona, Spain.
    • J Emerg Med. 2023 Jul 1; 65 (1): 161-6.

    BackgroundUrinary tract infections (UTI) due to multidrug-resistant bacteria are a frequent reason for visiting the emergency department (ED).ObjectivesThe aim of this study was to evaluate the applicability of a predictive model of infection by multidrug-resistant microorganisms in UTIs treated in an ED.MethodsThis is a retrospective observational study. Adult patients admitted to an ED with a diagnosis of UTI and positive urine culture were included. The main objective was to evaluate the area under the curve of the receiver operating characteristic (AUC-ROC), the scale proposed by González-del-Castillo, considering infection by a resistant pathogen as the dependent variable and the scale score of the predictive model used as the independent variable.ResultsThe study included 414 patients with UTIs, 125 (30.2%) of which were caused by multidrug-resistant microorganisms. A total of 38.4% of patients were treated with antibiotics during the previous 3 months and a multidrug-resistant pathogen was isolated from 10.4% of the total during the previous 6 months. The AUC-ROC of the scale for predicting UTIs due to multidrug-resistant microorganisms was 0.79 (95% confidence interval 0.76-0.83), the optimal cut-off point being 9 points, with a sensitivity of 76.8% and a specificity of 71.6%.ConclusionsThe use of the predictive model evaluated is a useful tool in real clinical practice to improve the success of empirical treatment of patients presenting to the ED with a diagnosis of UTI and positive urine culture pending identification.Copyright © 2023 Elsevier Inc. All rights reserved.

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