Efficiency of the estimation of physiologic ability and surgical stress (E-PASS) score in predicting postoperative complications after robot-assisted radical prostatectomy.

Abstract

Background: Robot-Assisted Radical Prostatectomy (RARP) is increasingly becoming the standard surgical treatment for prostate cancer. While some risk factors for postoperative complications of RARP have been identified, no scoring model that incorporates both preoperative physical status of the patient and intraoperative risk factors has been developed. The Estimation of Physiologic Ability and Surgical Stress (E-PASS) score was initially described to predict postoperative complications after gastrointestinal surgical procedures. This study aims to assess the effectiveness of the E-PASS score in predicting postoperative complications of RARP.

Methods: A retrospective evaluation was conducted on 204 patients who underwent RARP between 2019 and 2022. Demographic data, parameters indicating patients' preoperative physical condition, and intraoperative risk factors were analyzed. The E-PASS score and subscores were calculated for each patient.

Results: Of the patients, 164 (80.4%) were discharged without any postoperative complications (Group 1), and 40 (19.6%) experienced various degrees of complications (Group 2). Patients in Group 2 had higher rates of previous abdominal surgery, elevated Eastern Cooperative Oncology Group (ECOG) performance scores, longer surgical durations, and higher E-PASS scores. To assess the effectiveness of the Comprehensive Risk Score (CRS) as a predictive factor for postoperative complications, a receiver operating characteristic (ROC) curve was constructed with a 95% confidence interval (CI), and a cut-off value was established. The cut-off value for CRS was determined to be -0.0345 (area under the curve [AUC]=0.783, CI: 0.713-0.853; p<0.001). Patients with a CRS higher than the cut-off value had a 16.4 times higher rate of postoperative complications after RARP (95% CI: 5.58-48.5).

Conclusion: The E-PASS scoring model successfully predicts postoperative complications in patients undergoing RARP by using preoperative data about the physical status of the patient and surgical risk factors. The E-PASS score and its subscores could be utilized as objective criteria to determine the risk of postoperative complications before and immediately after surgery.