THE AMERICAN COLLEGE OF SURGEONS-NATIONAL SURGICAL QUALITY IMPROVEMENT PROGRAM CALCULATOR AND SURGICAL APGAR AS PREDICTORS OF POST-CHOLECYSTECTOMY COMPLICATIONS - Diana Tejeda-Herrera; Jose Caballero-Alvarado; Carlos Zavaleta-Corvera (ABCD: Arquivos Brasileiros de Cirurgia Digestiva)
ABSTRACT BACKGROUND: Laparoscopic cholecystectomy is considered safe; however, it is not free from complications, such as bile duct injuries, bleeding, and infection of the surgical site. AIMS: The aim of this study was to determine the effectiveness of two prediction tools, the American College of Surgeons-National Surgical Quality Improvement Program (ACS-NSQIP) calculator and the surgical Apgar, in predicting post-cholecystectomy complications. METHODS: A cross-sectional, analytical, and comparative study was conducted on patients over 18 years old diagnosed with acute cholecystitis who underwent open or laparoscopic cholecystectomy at the Regional Teaching Hospital of Trujillo between 2015 and 2019. A chi-square test was used for bivariate analysis, and the receiver operating characteristic (ROC) curve analysis was employed to determine the discriminative capacity of the ACS-NSQIP and surgical Apgar calculators in predicting severe complications. RESULTS: A total of 227 patients were included in the study. The analysis revealed that the mean age of patients who experienced severe complications was 75.32±4.58 years. Additionally, 52.6% of these patients were male. Regarding the prediction analysis based on the ROC curve, the ACS-NSQIP calculator showed an area under the curve of 0.895 (95%CI 0.819–0.971; p=0.01), whereas the surgical Apgar calculator showed an area under the curve of 0.611 (95%CI 0.488–0.735; p=0.11). CONCLUSIONS: The obtained results indicate that the ACS-NSQIP calculator is effective in predicting severe complications in patients undergoing cholecystectomy due to acute cholecystitis. These findings may have important implications for clinical practice and medical decision-making, focusing on the appropriate use of prediction tools to improve outcomes in this type of surgical procedure.