Development and validation of a novel nomogram for predicting systemic inflammatory response syndrome's occurrence in patients undertaking flexible ureteroscopy.

Background: The occurrence of systemic inflammatory response syndrome (SIRS) is an early alert for sepsis after flexible ureteroscopy (fURS). Once sepsis occurs, it often leads to severe or fatal consequences. We aimed to identify SIRS patients preoperatively by developing and validating a feasible prognostic nomogram model based on retrospective cohort analysis. Methods: A total of 311 patients who underwent fURS in Dongguan Kanghua Hospital (Dongguan, China) between 2016 and 2020 were included and randomly divided into a primary cohort (n=219) and validation cohort (n=92). Single factor regression analysis was used to identify the primary cohort's meaningful characters between SIRS and non-SIRS groups. Factors of the primary cohort were then identified by least absolute shrinkage and selection operator (LASSO) regression analysis, and a nomogram was built to execute the subsequent analysis using these factors. Finally, we analyzed and drew the calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) curve to validate the prognostic value of the nomogram in calibration and discrimination. Results: Review of the single regression analysis of characters in the primary cohort showed gender, stone burden, diabetes, neutrophil (N), lymphocyte (L), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocytes ratio (LMR), urine-WBC, nitrite (Nit), urine culture, and surgery time as significant factors between the SIRS and non-SIRS groups (P<0.05). The LASSO regression analysis suggested NLR, PLR, and urine culture were substantial factors in predicting SIRS postoperatively, lambda.min and lambda.1se (standard error, SE) were 0.01491 and 0.0796. A nomogram built with the three factors showed good calibration and discrimination, with the Brier values 0.064 and 0.034 and the area under curve (AUC) values 0.897 (95% CI: 0.837-0.957) and 0.976 (95% CI: 0.947-1.000) in the primary and validation cohort, respectively. DCA demonstrated the nomogram was clinically useful, and the predict probability of SIRS's occurrence was very close to the actual rate as the risk threshold increased by higher than 60% in clinical impact curve analysis. Conclusions: NLR, PLR, and urine culture were significantly related to the occurrence of SIRS's after fURS. The nomogram with these three factors showed excellent calibration, discrimination, and clinical usefulness.