ArticleInfection and drug resistance2025
Pathogen Resistance and Biomarker-Based Diagnosis of Postoperative Urinary Tract Infections in Kidney Stone Patients.
Article in Infection and drug resistance, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Albumin-to-Globulin Ratio as a Predictor of Disease Severity in Emergency Department Patients Presenting with Flank Pain.International journal of general medicine · 2026Article
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3 authors.
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Abstract
Background: Urinary tract infections (UTIs) are postoperative complications following kidney stone surgery, especially in regions with increasing antimicrobial resistance (AMR). In China, high resistance rates of uropathogens to commonly used antibiotics pose major challenges for effective treatment. This study aimed to investigate the pathogen spectrum, antimicrobial resistance patterns, and diagnostic utility of inflammatory biomarkers in postoperative UTIs among patients with kidney stones. Methods: This prospective observational study was conducted at a tertiary hospital in China, enrolling 130 patients who underwent kidney stone surgery between February 2021 and December 2024. Based on postoperative infection status, patients were classified into UTI (n=41) and Non-UTI groups (n=89). Blood samples were collected to assess inflammatory markers, including high-sensitivity C-reactive protein (hs-CRP), heparin-binding protein (HBP), neutrophil gelatinase-associated lipocalin (NGAL), and adiponectin (ADPN). Midstream urine samples from UTI patients were cultured for pathogen identification and antimicrobial susceptibility testing. Pearson correlation, receiver operating characteristic (ROC) analysis, and multivariate logistic regression were performed. Results: A total of 67 isolates were identified, mainly Gram-negative bacteria [59.70%; Conclusion: Postoperative UTIs in kidney stone patients are dominated by resistant Gram-negative bacteria. Combined biomarker detection (hs-CRP HBP, NGAL, ADPN) provides a reliable model for early infection diagnosis and risk stratification, supporting clinical decision-making.
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