Evaluating the Emergency Surgery Score (ESS) in Predicting Postoperative Outcomes Following Emergency Laparotomy: Insights From an Indian Tertiary Center.

Abstract

To determine the predictive value of Emergency Surgery Score (ESS) with regard to mortality and morbidity rates of patients undergoing emergency laparotomy. The ESSranging from 0 to 29 is an extensive risk calculator based on 22 variables including important parameters like demographics, preoperative treatment, comorbidities, and laboratory values. Twenty patients who underwent emergency laparotomy were preoperatively assessed and ESS was calculated for each. After establishment of diagnosis and resuscitation, the patient was taken up for emergency laparotomy. Postoperatively, patients were monitored clinically as well as with laboratory and radiological investigations as per case needed till discharge and further followed up physically in OPD/ward or interviewed telephonically for 30 days on a weekly basis. Incidence of mortality and morbidity in terms of postoperative complications, ICU admission, reoperation and readmission among the cases occurring within 30 days of procedure were recorded. ESS correlated well with the outcome in the current study, 10 out of 14 patients with score less than 8 were discharged without any complications. Mean ESS was higher among non-survivors. Ability of ESS to predict postoperative mortality, morbidity and ICU stay was proven statistically with c-statistics of 0.853, 0.84, 0.879 respectively. ESS was found to be a good predictor for the development of postoperative lower respiratory tract infection (LRTI) (c-statistic=0.828), sepsis (c-statistic=0.867), disseminated intravascular coagulation (DIC) (c-statistic=0.805), acute kidney injury (AKI) (c-statistic=0.804). ESS showed poor correlation with reoperation and readmission rates. The current study underscores the critical importance of employing risk stratification throughESSfor patients undergoing emergency laparotomy. By employing ESS, healthcare professionals can accurately anticipate resuscitation requirements and stabilize patients preoperatively. This proactive approach enables the identification and optimization of patients unsuitable for immediate surgery, facilitating informed decisions on targeted treatment, surgical intervention, and postoperative care pathways.