Development and validation of a nomogram combining cytokines with traditional clinical parameters in predicting the risk of postoperative sepsis after ureteroscopic lithotripsy.

Background: Sepsis is one of the most severe complications of ureteroscopic lithotripsy (URSL) surgery and is the main cause of death in hospitalized patients. Traditional preoperative patient management and risk assessment systems need to be updated urgently to reduce the occurrence of postoperative sepsis. This study aimed to construct a novel nomogram to preoperatively predict the risk of septic complications after URSL.

Method: We retrospectively reviewed the records of patients who underwent URSL between January and December 2023 and divided them into the control and sepsis groups according to their postoperative outcomes. Baseline data, routine blood and urine parameters, and blood cytokine concentrations were collected for analysis. Independent predictive factors for the onset of postoperative sepsis were selected using univariate and multivariate logistic regression analyses. A nomogram was constructed, and its clinical effectiveness was validated using receiver operating characteristic (ROC) curve and decision curve analyses (DCA).

Results: Three hundred and thirty-three patients were included in the analysis; 293 were discharged smoothly and divided into a control group, and 40 patients developed postoperative sepsis. Day of preoperative antibiotic use, C-reactive protein, albumin, lactate dehydrogenase, interleukin (IL)-6, IL-8, IL-10, interferon-γ, and urine protein were entered into the nomogram. Our nomogram demonstrated strong discriminative ability, with an area under the ROC curve of 0.981. Further validation of the DCA showed that the nomogram was clinically useful in evaluating the risk of postoperative septic complications.

Conclusions: We developed a nomogram combining traditional blood and urine parameters with cytokine concentrations to predict the risk of postoperative septic complications after URSL. Validation using decision curve analysis revealed satisfactory discrimination, indicating its potential clinical utility. This may aid in surgical risk assessment and clinical decision-making.