Older patient age and prior antimicrobial use strongly predict antimicrobial resistance in Escherichia coli isolates recovered from urinary tract infections among female outpatients.

Mitrani-Gold FS, Kaye KS, Gupta V, Mulgirigama A, Trautner BW, Scangarella-Oman NE, Yu KC, Ye G, Joshi AV. Older patient age and prior antimicrobial use strongly predict antimicrobial resistance in Escherichia coli isolates recovered from urinary tract infections among female outpatients. PLoS ONE. 2023 May 11; 18(5):e0285427.

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Abstract:

BACKGROUND: Increasing prevalence of antimicrobial resistance (AMR), including multidrug resistance (MDR), among Escherichia coli (E. coli) makes treatment of uncomplicated urinary tract infection (uUTI) difficult. We assessed risk factors for fluoroquinolone (FQ)-not-susceptible (NS) and MDR E. coli among US female outpatients. METHODS: This retrospective cohort study utilized data from female outpatients aged 12 years with E. coli positive urine culture and oral antimicrobial prescription ± 1 day from index. We assessed patient-level factors within 90 and 91-360 days prior to index as predictors of FQ NS (intermediate/resistant) and MDR (NS to 1 drug across 3 classes) E. coli: age, prior oral antimicrobial dispensing, prior AMR phenotypes, prior urine culture, and prior hospitalization. RESULTS: Among 1,858 outpatients with urine-isolated E. coli, 369 (19.9%) had FQ NS and 59 (3.2%) had MDR isolates. After multivariable adjustment, independent risk factors (p < 0.03) for FQ NS E. coli were older age, prior FQ NS isolates, prior dispensing of FQ, and dispensing of any oral antibiotic. Independent risk factors (p < 0.02) for MDR were prior extended-spectrum -lactamase-producing isolates (ESBL+), prior FQ dispensing, and prior oral antibiotic dispensing. CONCLUSIONS: In women with uUTI due to E. coli, prior dispensing of FQ or any oral antibiotic within 90 days predicted FQ NS and MDR urine E. coli. Prior urine culture with FQ NS isolates and older age were predictive of FQ NS E. coli. Prior ESBL+ was predictive of MDR E. coli. These data could help identify patients at risk for AMR E. coli and inform empiric prescribing.