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Impact of Multidrug-Resistant Uropathogens on Mortality in Elderly Patients with Urinary Tract Infections: A
Pınar Yürük Atasoy1, Sevil Alkan2, Dilek Bulut3
1Department of Infectious Diseases and Clinical Microbiology, Ankara Bilkent City Hospital, Ankara 06502, Turkey.
Abstract:
Background/Objectives: Urinary tract infections (UTIs) in older adults are common and potentially life-threatening conditions that often present with atypical symptoms. Early identification of prognostic factors is essential to improve clinical outcomes and reduce mortality in this vulnerable population. Methods: This retrospective, multicenter study included patients aged ≥65 years who were hospitalized with a diagnosis of UTI between January 2019 and December 2023. Diagnoses were established by infectious disease specialists based on clinical findings and microbiological confirmation in accordance with international guidelines. Only patients with urine cultures showing ≥100,000 CFU/mL bacterial growth were included. Demographic, clinical, laboratory, and microbiological data were analyzed. Multivariable logistic regression was used to identify independent predictors of in-hospital mortality. Results: A total of 1175 patients (median age: 75 years; 51.1% male) were included. The in-hospital mortality rate was 14.6%, and 25.6% required intensive care unit (ICU) admission. Multidrug-resistant (MDR) bacteria were detected in 63.6% of isolates, and bacteremia was present in 24.3% of cases. In multivariable analysis, MDR/ESBL positivity (OR: 2.09, 95% CI: 1.24-3.50, p = 0.005), bacteremia (OR: 2.10, 95% CI: 1.32-3.35, p = 0.002), and SOFA score (OR: 1.53, 95% CI: 1.42-1.65, p < 0.001) were independently associated with in-hospital mortality. Age and altered mental status were also significant predictors, while CRP and procalcitonin lost significance after adjustment. Conclusions: UTIs in elderly patients are associated with substantial morbidity and mortality. Multidrug-resistant pathogens, bacteremia, and disease severity play a central role in determining outcomes. Early identification of high-risk patients using clinical severity scores and microbiological data may improve risk stratification and guide timely, targeted therapeutic interventions.
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