Prediction of complications after laparoscopic partial nephrectomy: feasibility of E-PASS score

Abstract

Purpose With significant advancements in laparoscopic procedures and tools over the last decade, the partial nephrectomy (PN) surgical approach has gradually transformed from open to laparoscopic partial nephrectomy (LPN). Although numerous studies evaluating the postoperative complications of laparoscopic partial nephrectomy can be found in the literature, a scoring system that addresses both preoperative physical condition and intraoperative risk factors has not yet been established. The Estimation of Physiological Ability and Surgical Stress (E-PASS) score is a scoring system that considers both the patient's preoperative condition and intraoperative variables to predict the risk of postoperative complications in surgically treated patients. This study aimed to assess the applicability of the E-PASS scoring system for predicting postoperative complications following LPN. Methods We analyzed data of 196 patients who underwent LPN between 2017 and 2024 by a single surgeon in this single-center retrospective study. Demographic data of the patients, parameters reflecting patients' preoperative physical condition, and intraoperative risk factors were recorded. Postoperative complications were classified using the Clavien-Dindo system. The E-PASS score and its sub-scores were calculated for each patient. ResultsVarious degrees of complications developed in 46 patients (23.5%). Patients who developed complications had significantly higher mean age, performance scores, tumor sizes, length of hospital stay, and E-PASS values. The cutoff value of the E-PASS Comprehensive Risk Score (CRS) for predicting the development of postoperative complications was determined to be - 0.1692 (AUC = 0.676; 95% CI 0.581-0.771; p < 0.001). According to the results of the multivariate analysis, the presence of E-PASS CRS > - 0.1692 (OR 4.872; 95% CI 2.384-9.957; p < 0.001) and tumor size (OR 1.021; 95% CI 1-1.041; p = 0.047) was identified as independent risk factors predicting postoperative complications. Patients with a CRS higher than the cutoff value had a 4.87 times higher rate of postoperative complications after LPN. Conclusion The E-PASS scoring model successfully predicts postoperative complications in patients undergoing LPN by utilizing preoperative data on the patient's physical condition and surgical risk factors. The E-PASS score and its sub-scores can serve as objective criteria to determine the risk of postoperative complications both preoperatively and immediately postoperatively.