Abstract
OBJECTIVES: To analyze the association of serum heparin-binding protein (HBP) and C-reactive protein (CRP) levels with urosepsis following flexible ureteroscopic lithotripsy (FURL) and to construct a back propagation neural network prediction model. METHODS: A total of 428 patients with kidney stones who underwent FURL were enrolled. Patients were divided into sepsis group (n=42) and control group (n=386) according to whether post-operative urosepsis developed. Logistic regression analysis was used to determine the risk factors of post-FURL urosepsis and their interactions. A logistic regression model and a back propagation neural network model were developed for predicting post-FURL urosepsis following FURL, and their predictive performance was evaluated using receiver operating characteristic curves. RESULTS: Univariate analysis showed that stone surgery history, gender, positive urine culture, stone diameter, diabetes, operation time, white blood cell (WBC), platelet, CRP, and HBP levels were significantly associated with post-FURL urosepsis (all P<0.05). Multivariate analysis identified positive urine culture, CRP, and HBP levels as independent risk factors for post-FURL urosepsis (all P<0.05). Interaction analysis revealed that CRP and HBP showed both additive (RERI=8.453, 95%CI: 2.645-16.282; AP=0.696, 95%CI: 0.131-1.273; S=3.369, 95%CI: 1.176-7.632) and multiplicative (OR=1.754, 95%CI: 1.218-3.650) interactions, while CRP and urine culture demonstrated multiplicative interaction (OR=2.449, 95%CI: 1.525-3.825). The back propagation neural network model demonstrated superior predictive performance compared to the logistic regression model. CONCLUSIONS: CRP and HBP levels are independent risk factors for post-FURL urosepsis. The back propagation neural network model based on CRP and HBP exhibits higher predictive accuracy than the logistic regression model, which may provide a reliable risk assessment tool for early discrimination and intervention of post-FURL urosepsis.