The following is a summary of “PREDICTION OF MULTIDRUG-RESISTANT BACTERIA IN URINARY TRACT INFECTIONS IN THE EMERGENCY DEPARTMENT,” published in the July 2023 issue of Emergency Medicine by Ruiz-Ramos et al.

Urinary tract infections (UTIs) caused by bacteria resistant to multiple drugs are a common cause for seeking medical attention at the emergency department (ED). This study aimed to assess the feasibility of utilizing a predictive model to detect infection caused by multidrug-resistant microorganisms in urinary tract infections managed in an emergency department. This is a retrospective observational study conducted in a medical context. Adult patients admitted to an Emergency Department (ED) diagnosed with urinary tract infection (UTI) and positive urine culture were enrolled. 

The primary aim was to assess the area under the curve of the receiver operating characteristic (AUC-ROC), as proposed by González-del-Castillo, with the dependent variable of infection caused by a resistant pathogen, while considering the independent variable of the scale score from the predictive model utilized. The research involved 414 individuals diagnosed with urinary tract infections (UTIs), 125 cases (30.2%) attributed to multidrug-resistant microorganisms. 38.4% of individuals received antibiotic treatment within the preceding 3 months, while a multidrug-resistant pathogen was identified in 10.4% of the population within the preceding 6 months. 

The area under the receiver operating characteristic curve (AUC-ROC) of the scale for predicting urinary tract infections (UTIs) caused by multidrug-resistant microorganisms was 0.79 (95% confidence interval 0.76–0.83). The optimal cut-off point was 9, with a sensitivity of 76.8% and a specificity of 71.6%. Using the predictive model assessed is a valuable tool in medical practice to enhance the efficacy of empirical treatment for patients arriving at the emergency department with a diagnosed urinary tract infection (UTI) and a pending urine culture for identification.

Source: sciencedirect.com/science/article/abs/pii/S0736467923002317