The incremental value of a novel immuno-inflammatory index (SIICI) in predicting sepsis after ureteroscopic lithotripsy: development and validation of a nomogram

Background: Sepsis continues to be a life-threatening complication following ureteroscopic lithotripsy (URSL). Available clinical prediction tools tend to be inadequate in their capacity to depict the underlying pathophysiology of sepsis-systemic immune-inflammatory imbalance. It is particularly difficult in patients who lack obvious preoperative microbiological findings. The study aims to evaluate the new Systemic Immune-Inflammatory Complex Index (SIICI) as well as other indices such as (SII, SIRI, PIV) in predicting post-URSL sepsis. Methods: We performed a single-center retrospective study of 803 patients who underwent URSL. Multivariate logistic regression was used to create a clinical baseline model. To assess the incremental predictive value, each inflammatory index was added separately to the baseline model. The model performance was compared using the area under the ROC curve (AUC), net reclassification improvement (NRI), integrated discrimination improvement (IDI), likelihood ratio test (LRT) and decision curve analysis (DCA). Results: The "Base + SIICI" model was found to be the most effective among the four indices. It had the highest degree of discrimination (AUC = 0.863, 95% CI: 0.819-0.908), which is a considerable improvement over the baseline model (AUC = 0.807, p