Construction and validation of the nomogram predictive model for post-percutaneous nephrolithotomy urinary sepsis

• Published in: World journal of urology 2024-03, Vol.42 (1), p.135-135, Article 135
• Main Authors: Qiu, Zuze, Zhan, Shun, Song, Yuanming, Huang, Liang, Xie, Jing, Qiu, Tao, Zhao, Changyong, Wang, Leibo, Li, Daobing
• Format: Article
• Language: English
• Subjects: Medicine; Medicine & Public Health; Nephrology; Nomograms; Oncology; Original Article; Patients; Prediction models; Regression analysis; Risk factors; Sepsis; Statistical analysis; Urological surgery; Urology
• ISSN: 1433-8726; 0724-4983; 1433-8726
• DOI: 10.1007/s00345-024-04828-2

Objective This study aimed to construct and validate a simple and accurate clinical nomogram for predicting the occurrence of post-percutaneous nephrolithotomy sepsis, aiming to assist urologists in the early identification, warning, and early intervention of urosepsis, and to provide certain evidence-based medicine basis. Methods This study included patients who underwent PCNL surgery due to kidney or upper ureteral stones at the Department of Urology, Affiliated Hospital of Zunyi Medical University, from January 2019 to September 2022. This study utilized univariate and multivariate logistic regression analysis to screen and evaluate the risk factors for sepsis and construct a predictive model. An evaluation was performed using the receiver operating characteristic curve, calibration curve, and decision curve analysis curve. All statistical analyses were conducted using R version 4.2. Results A total of 946 patients who underwent post-PCNL were included in this study, among whom 69 patients (7.29%) developed post-PCNL urinary sepsis. Multiple-factor logistic regression analysis identified four independent risk factors associated with post-PCNL urinary sepsis, including positive urinary nitrite (OR = 5.9, P