Urinary tract infections (UTIs) are the most common bacterial infection treated in primary care clinics. Selection of therapy for UTIs treated in these settings is empiric and typically based on clinical signs and symptoms, medical history, urinalysis, and population-level data of the prevalence of antimicrobial resistance. Despite availability and appropriateness of first-line antibiotics, use of broader spectrum, second-line agents such as fluoroquinolones have increased significantly over the last decade. This has contributed to increased antimicrobial resistance, making these agents less viable treatment options for other serious infections. The overall objective of this application, which represents the next step toward our long-term goal, is to develop a risk score for guiding prudent empiric selection of antibiotic therapy for uncomplicated UTI in women treated in primary care settings. Our central hypothesis is that specific patient characteristics and medical history can be used to identify UTI patients at high risk for infection due to trimethoprim/sulfamethoxazole (TMP/SMX)- resistant Enterobacteriaceae. Therefore, the rationale for this project is that empiric treatment o UTIs with fluoroquinolones can be better directed towards this high risk population by identifying patients most likely to have TMP/SMX-resistant infection. We plan to test our central hypothesis and accomplish the objective of this application by pursuing two specific aims: (1) Develop and validate a risk score to inform empiric antibiotic prescribing in adult female patients with uncomplicated UTI by identifying those at higher risk of infection due to TMP/SMX-resistant Enterobacteriaceae and (2) Establish the feasibility of using the risk score as a decision aid in primary care clinics by prospectively evaluating patient safety and scientific validity. The expected outcome is a validated risk score for identifying UTI patients at high risk of infection due to TMP/SMX-resistant Enterobacteriaceae that can be safely tested for effectiveness in primary care settings through a larger scale prospective study. Long-term, such a tool is expected to have a positive impact on the ecology of antibiotic- resistant bacteria by decreasing the evolutionary selective pressures driving the emergence of multi-drug resistant organisms. This is significant because prudent and appropriate antibiotic use is critical to preserving existing antibiotics as viable treatment options.
This project aims to improve how doctors select antibiotics to treat urinary tract infections during an office visit. By using patient characteristics (e.g., demographics, medical history, previous antibiotic prescriptions, etc.), we will develop a tool tha will enable doctors to better select which is the best drug to prescribe. This issue is important because some antibiotics used for urinary tract infections are being over- prescribed, which can lead to increased multidrug-resistant organisms.