Nomogram based on preoperative systemic immune-inflammation index for Post-Anesthesia Care Unit duration predication in renal cancer patients underwent Robot-assisted partial nephrectomy

Background Accurate and timely discharge from the Post-Anesthesia Care Unit (PACU) is crucial for preventing postoperative complications and optimizing hospital resource utilization. This study aimed to develop a preoperative nomogram incorporating inflammatory markers and clinical characteristics to predict anesthesia recovery time in patients with renal cell carcinoma (RCC) undergoing robot-assisted partial nephrectomy (RAPN). Methods A nomogram was developed to identify significant predictors of anesthesia recovery time in a retrospective cohort of 218 patients under general anesthesia for RCC between December 2023 and April 2025. Based on preoperative covariates and multivariable Cox proportional hazards regression, the model estimates the probability of discharge from the post-anesthesia care unit (PACU) at 35, 45, and 55 minutes. Validation of the nomogram was performed using the concordance index (C-index), calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA). Results Age, RENAL score, monocyte count, and systemic immune-inflammation index (SII) were identified as independent predictors and incorporated into the nomogram. The model demonstrated strong predictive performance for PACU duration at all three time points. The C-index values were 0.816 for the training cohort and 0.835 for the validation cohort. ROC analysis, calibration plots, and DCA all indicated satisfactory discrimination and clinical utility. Furthermore, the nomogram showed superior predictive performance compared to a model based solely on age and RENAL score. Risk stratification based on nomogram scores categorized patients into two distinct groups with significantly different recovery times. Conclusions The nomogram developed in this study exhibits strong predictive accuracy for estimating anesthesia recovery time, showing promise as a practical tool for assessing PACU discharge readiness. Further research is warranted to validate its clinical utility and potential to enhance patient outcomes and operational efficiency. Trial registration This study is a retrospective study.