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已发表论文
肾结石患者术后尿路感染的病原体耐药特征与生物标志物诊断研究
Authors Shen L, Zheng Y, Jiang X
Received 28 April 2025
Accepted for publication 1 November 2025
Published 8 November 2025 Volume 2025:18 Pages 5829—5841
DOI https://doi.org/10.2147/IDR.S537247
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Sara Mina
Lilei Shen,1 Yi Zheng,2 Xingxin Jiang1
1Department of Laboratory Medicine, Suzhou Hospital of Integrated Traditional Chinese and Western Medicine, Suzhou, 215101, People’s Republic of China; 2Department of Laboratory Medicine, The Second Affiliated Hospital of Soochow University, Suzhou, 215004, People’s Republic of China
Correspondence: Xingxin Jiang, Department of Laboratory Medicine, Suzhou Hospital of Integrated Traditional Chinese and Western Medicine, No. 39 Xiashatang, Mudu Town, Wuzhong District, Suzhou, Jiangsu, 215101, People’s Republic of China, Email 13814854733@163.com
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%; Escherichia coli (E. coli), Pseudomonas aeruginosa (P. aeruginosa), Klebsiella pneumoniae (K. pneumoniae)], Gram-positive bacteria (32.84%), and fungi (7.46%). Most Gram-negative isolates showed > 85% resistance to AMP, while remaining sensitive to imipenem. UTI patients had higher white blood cell counts, hs-CRP, HBP, NGAL, and lower ADPN levels (all P< 0.001). Among biomarkers, HBP and ADPN showed high diagnostic value (AUC=0.8193 and 0.8719), and their combination with hs-CRP and NGAL achieved excellent accuracy (AUC=0.9496). HBP and NGAL were independent risk factors, while ADPN (OR=0.379, P< 0.001) was protective.
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.
Keywords: urinary tract infection, kidney stones, antimicrobial resistance, inflammatory biomarkers, adiponectin, HBP, diagnostic model
1Department of Laboratory Medicine, Suzhou Hospital of Integrated Traditional Chinese and Western Medicine, Suzhou, 215101, People’s Republic of China; 2Department of Laboratory Medicine, The Second Affiliated Hospital of Soochow University, Suzhou, 215004, People’s Republic of China
Correspondence: Xingxin Jiang, Department of Laboratory Medicine, Suzhou Hospital of Integrated Traditional Chinese and Western Medicine, No. 39 Xiashatang, Mudu Town, Wuzhong District, Suzhou, Jiangsu, 215101, People’s Republic of China, Email 13814854733@163.com
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%; Escherichia coli (E. coli), Pseudomonas aeruginosa (P. aeruginosa), Klebsiella pneumoniae (K. pneumoniae)], Gram-positive bacteria (32.84%), and fungi (7.46%). Most Gram-negative isolates showed > 85% resistance to AMP, while remaining sensitive to imipenem. UTI patients had higher white blood cell counts, hs-CRP, HBP, NGAL, and lower ADPN levels (all P< 0.001). Among biomarkers, HBP and ADPN showed high diagnostic value (AUC=0.8193 and 0.8719), and their combination with hs-CRP and NGAL achieved excellent accuracy (AUC=0.9496). HBP and NGAL were independent risk factors, while ADPN (OR=0.379, P< 0.001) was protective.
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.
Keywords: urinary tract infection, kidney stones, antimicrobial resistance, inflammatory biomarkers, adiponectin, HBP, diagnostic model