eP136 Enhancing Morbidity Prediction in Emergency Laparotomy: A Comparative Study of NELA and ACS Risk Calculators

Abstract Introduction Emergency laparotomy (EL) is a high-risk procedure often linked to significant morbidity and mortality. While efforts have reduced mortality in EL patients, limited research focuses on predicting and improving morbidity outcomes. Current tools like the National Emergency Laparotomy Audit (NELA) and the American College of Surgeons (ACS) calculators mostly estimate mortality risks, with less focus on morbidity. This study aims to compare the predictive accuracy of these calculators to address the gap in morbidity predictions for EL patients. Methods A descriptive cross-sectional study analyzed data from 330 patients who underwent emergency laparotomy from January 2021 to January 2023, using the Hospital NELA database. Patient characteristics, surgery type, estimated risk, and adverse events were assessed with SPSS version 26. Stepwise Multiple Linear Regression, Spearman and Pearson correlation coefficients, and Paired Sample T-tests were used to evaluate morbidity predictors and compare outcomes. Results The study found significant discrepancies between the NELA and ACS morbidity predictions. NELA overestimated both preoperative (Mean = 70.17, SD = 23.14) and postoperative morbidity (Mean = 70.58, SD = 24.23), compared to ACS (Mean = 33.20, SD = 15.55), which was much higher than the actual observed morbidity (Mean = 1.37, SD = 0.49). No significant correlation was found between morbidity predictions, although a moderate correlation was noted for hospital stay predictions (r = 0.560, p < 0.001). Conclusion This study underscores the need for improved morbidity prediction tools in EL. NELA significantly overestimates morbidity, highlighting the importance of refining these models to better guide clinical decisions.