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Emergency Surgery Score Accurately Predicts the Risk of Post-Operative Infection in Emergency General Surgery
Kelsey Han1, Jae Moo Lee1, Aditya Achanta1
1Division of Trauma, Emergency Surgery, and Surgical Critical Care, Massachusetts General Hospital , Boston, Massachusetts.
Background:
The Emergency Surgery Score (ESS) was validated recently as an accurate and user-friendly post-operative mortality risk calculator specific for Emergency General Surgery (EGS). ESS is calculated by adding one to three integer points for each of 22 pre-operative variables (demographics, co-morbidities, and pre-operative laboratory values); increasing scores accurately and gradually predict higher mortality rates. We sought to evaluate whether ESS can predict the occurrence of post-operative infectious complications in EGS patients.
Patients And Methods:
Using the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database from 2007-2015, all EGS patients were identified by using the "emergent" ACS-NSQIP variable and a concomitant surgery Current Procedural Terminology code for "digestive system." Patients with any missing ESS variables or those who died within 72 hours from the surgical procedure were excluded. A composite variable, post-operative infection, was created and defined as the post-operative occurrence of one or more of the following: superficial, deep incisional or organ/space surgical site infection, surgical site disruption, pneumonia, sepsis, septic shock, or urinary tract infection. ESS was calculated for all included patients, and the correlation between ESS and post-operative infection was examined using c-statistics.
Results:
Of a total of 4,456,809 patients, 90,412 patients were included. The mean age of the population was 56 years, 51% were female, and 70% were white; 22% developed one or more post-operative infections, most commonly sepsis/septic shock (12.2%), surgical site infection (9%), and pneumonia (5.7%). The ESS gradually and consistently predicted infectious complications; post-operative infections developed in 7%, 24%, and 49% of patients with an ESS of 1, 5, and 10, respectively. The c-statistics for overall post-operative infection, post-operative sepsis/septic shock, and pneumonia were 0.73, 0.75, and 0.80, respectively.
Conclusion:
The ESS accurately predicts the occurrence of post-operative infectious complications in EGS patients and could be used for pre-operative clinical decision-making as well as quality benchmarking of infection rates in EGS.
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