Epidemiology and antimicrobial resistance of uropathogens in a tertiary care setting in Yemen: a retrospective study

Background: Urinary tract infections (UTIs) are a major global health concern, particularly in resource-limited regions where antimicrobial resistance (AMR) is increasingly prevalent. This study aimed to describe the demographic characteristics, pathogen distribution, and antimicrobial resistance patterns among UTI patients, and to identify clinical predictors of multidrug-resistant (MDR) and extensively drug-resistant (XDR) infections.
Methods: A retrospective analysis was conducted on 216 clinically confirmed UTI cases processed at the Infectious Bacteriology and Biochemistry Laboratory affiliated with IBB University between January 2023 and September 2024. Data collected included patient demographics, clinical symptoms, comorbidities, bacterial isolates, and antimicrobial susceptibility profiles. MDR and XDR were classified according to internationally recognized definitions. Univariate and multivariate logistic regression analyses were performed to identify independent predictors of MDR/XDR infections.
Results: The majority of patients were adults aged 15-65 years (83.3%, n=180), with a slight male predominance (53.2%, n=115). Escherichia coli was the most frequently isolated pathogen (29.6%, n=64), followed by Staphylococcus aureus (19.0%, n=41) and Pseudomonas aeruginosa (6.0%, n=13). A substantial proportion of isolates exhibited MDR or XDR phenotypes (80.1%, n=173). Among E. coli isolates, resistance rates to ciprofloxacin and ceftriaxone exceeded 60%. Notably, all Klebsiella pneumoniae isolates were MDR (100%), and 92.3% of P. aeruginosa isolates were MDR. Nitrofurantoin and carbapenems demonstrated relatively higher susceptibility rates. Multivariate analysis identified prior hospitalization (adjusted odds ratio [aOR] = 3.15; 95% CI:1.50-6.60; p=0.002) and E. coli infection (aOR = 2.41; 95%CI: 1.02–5.70; p=0.04) as significant predictors of MDR/XDR infections.
Conclusions: The high prevalence of MDR and XDR uropathogens, particularly E. coli, underscores the urgent need for sustained antimicrobial resistance surveillance and stewardship programs in resource-limited settings. Identifying key clinical predictors can inform empirical treatment strategies, improve patient outcomes, and help contain the spread of resistant organisms.

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