Low-inflammatory response phenotypes in elderly urinary tract infections: pathogen type, antimicrobial resistance, and comorbidity-associated risk profiles

Urinary tract infections (UTIs) in elderly patients often present with attenuated inflammatory responses, complicating diagnosis and treatment. This retrospective cohort study analyzed 1,950 hospitalized patients aged ≥ 60 years (2022–2024) to investigate associations between uropathogens, antimicrobial resistance, urinary inflammatory markers (pyuria, leukocyte esterase, nitrite), and comorbidities. Standard culture, VITEK2 identification, and Clinical and Laboratory Standards Institute (CLSI) guidelines were used for pathogen characterization. Logistic regression models assessed risk factors for resistance and inflammation, while clinical outcomes were compared between susceptibility-matched and mismatched therapies. Escherichia coli dominated (62.7%) and elicited the strongest inflammatory responses, with pyuria (59.8%), leukocyte esterase (82.6%), and nitrite positivity (47.8%; all P < 0.001 compared with other pathogens). Enterococcus spp. (9.5%) and resistant strains (29.9%) showed significantly weaker inflammation: resistant isolates had lower pyuria (68.0% vs. 83.8%) and leukocyte esterase positivity (64.6% vs. 84.2%; P < 0.001). Diabetes independently increased risks of extended-spectrum β-lactamase (ESBL)-producing (OR = 1.87, 95% CI:1.50–2.33) and carbapenem-resistant Enterobacteriaceae (CRE) infections (OR = 2.01, 1.32–3.05), while chronic kidney disease correlated with Enterococcus prevalence (OR = 2.35, 1.54–3.59). Patients receiving susceptibility-matched therapy had shorter hospital stays (median 6 vs. 9 days, P = 0.025) and lower sepsis incidence (5.9% vs. 9.7%, P = 0.016). These findings reveal pathogen-specific inflammatory signatures in elderly UTIs, with resistant organisms and Enterococcus spp. linked to diagnostically challenging low-inflammatory phenotypes. Comorbidities shape resistance risks, advocating for individualized diagnostic thresholds and rapid resistance profiling to optimize empirical therapy.