DERIVATION AND VALIDATION OF A NOVEL EMERGENCY SURGERY ACUITY SCORE (ESAS).

Background: There currently exists no pre-operative risk stratification system for Emergency Surgery (ES). We sought to develop an Emergency Surgery Acuity Score (ESAS) that helps predict perioperative mortality in ES patients. Methods: Using the 2011 American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database (derivation cohort), we identified all surgical procedures that were classified as "emergent". A three step methodology was then performed. First, multiple logistic regression models were created to identify independent predictors (e.g. patient demographics, co-morbidities, and pre-operative laboratory variables) of 30-day mortality in ES. Second, based on the relative impact of each identified predictor (i.e. Odds Ratio), using weighted averages, a novel score was derived. Third, using the 2012 ACS-NSQIP database (validation cohort), the score was validated by calculating its c-statistic and evaluating its ability to predict 30-day mortality. Results: From 280,801 NSQIP cases, 18,439 ES cases were analyzed, of which 1,598 (8.7%) resulted in death at 30 days. The multiple logistic regression analyses identified 22 independent predictors of mortality. Based on the relative impact of these predictors, ESAS was derived with a total score range of 0-29. ESAS had a c-statistic of 0.86; the probability of death at 30-day gradually increased from 0% to 36% then 100% at scores of 0, 11 and 22, respectively. In the validation phase, 19,552 patients were included, the mortality rate was 7.2% and the ESAS c-statistic stayed at 0.86. Conclusions: We have therefore developed and validated a novel score, ESAS, that accurately predicts mortality in ES patients. Such a score could prove useful for: 1) pre-operative patient counseling; 2) identification of patients needing close postoperative monitoring; and 3) risk-adjustment in any efforts at benchmarking the quality of ES. Level of Evidence: III Study Type: Prognostic and Epidemiological (C) 2016 Lippincott Williams & Wilkins, Inc.

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