Objective:To investigate the predictive value of the modified Estimation of Physiologic Ability and Surgical Stress (E-PASS) score system for anesthesia-related adverse events (ARAEs) in elderly patients (≥75 years) undergoing laparoscopic surgery, and to identify the independent risk factors for ARAEs in this patient population.Methods: This clinical study planned to enroll 60 elderly patients (≥75 years) who were scheduled for laparoscopic surgery in our hospital from January 2025 to December 2025. All patients underwent preoperative assessment using the modified E-PASS scoring system. General patient data and perioperative indicators were recorded. Patients were monitored for 72 hours postoperatively for the occurrence of ARAEs. Based on the incidence of ARAEs, patients were divided into an occurrence group (n=21) and a non-occurrence group (n=39). The differences in modified E-PASS scores and clinical indicators between the two groups were compared. Spearman rank correlation analysis was used to analyze the correlation between modified E-PASS scores and the severity of ARAEs. Receiver Operating Characteristic (ROC) curve analysis was employed to evaluate the predictive value of the modified E-PASS scores for ARAEs. Multivariate logistic regression analysis was used to screen for independent risk factors for ARAEs.Results:The incidence of ARAEs within 72 hours postoperatively was 35.00% (21/60) among the 60 patients. ROC curve analysis revealed that the Area Under the Curve (AUC) for Preoperative Risk Score (PRS), surgical stress score for the formula (SSSf), comprehensive risk score for the formula (CRSf), and the combined diagnosis were 0.783, 0.758, 0.626, and 0.862, respectively. Multivariate logistic regression analysis identified age, operation time, and CRSf as independent influencing factors for ARAEs in elderly patients (≥75years) undergoing laparoscopic surgery.Conclusion:The modified E-PASS scoring system has a high predictive value for ARAEs in elderly patients (≥75 years) undergoing laparoscopic surgery and can assist in the early clinical identification of high-risk patients. Furthermore, age, operation time, and CRSf are independent influencing factors that should be given special attention preoperatively to optimize perioperative management.