Longitudinal study reveals lower antibiotic costs with non-pathogenic urinary isolates, suggesting enhanced antimicrobial stewardship.
Background: Urinary tract infections (UTIs) are among the most common reasons for antibiotic prescriptions in hospitalized patients. However, distinguishing pathogenic from non-pathogenic urinary isolates remains challenging. The inappropriate treatment of colonizers and contaminants can result in unnecessary antimicrobial use, contributing to resistance, adverse events, and increased healthcare costs. Objective: This study aims to evaluate the economic impact of identifying non-pathogenic urinary isolates using a stepwise diagnostic model in hospitalized patients. Methods: In this longitudinal observational study conducted over 24 months at a tertiary care hospital, adult inpatients with positive urine cultures were assessed. A stepwise model integrating clinical, laboratory, and microbiological parameters was applied to classify isolates as pathogenic or non-pathogenic. Outcomes including antibiotic usage (duration and cost), 30-day mortality, and hospital stay length were compared between patients with pathogenic and non-pathogenic isolates. Results: Among 275 isolates, 249 (90.54%) were identified as pathogenic and 26 (9.45%) as non-pathogenic. Median antibiotic duration showed no significant difference (7 days (IQR: 5–7) for both groups). However, median antibiotic cost was significantly higher in the pathogenic group (Rs. 2440 vs Rs. 640; p < 0.001), with a large effect size (r = 0.48). The median hospitalization duration was similar between groups (12 days (interquartile range [IQR]: 7–19) vs 10 days (IQR: 5.25–17.75); p = 0.336). The 30-day mortality was 2.0% in the pathogenic group; no deaths were reported in the non-pathogenic group. Conclusion: Recognizing non-pathogenic isolates can reduce inappropriate antibiotic use and associated costs without adversely affecting patient outcomes. Implementation of such a diagnostic approach can strengthen antimicrobial stewardship programs and improve healthcare efficiency.
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Yadav et al. (2025) studied this question.
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