Predictors of mortality following emergency general surgery: An American College of Surgeons National Surgical Quality Improvement Program risk calculator.

Background: The complex nature of current morbidity and mortality predictor models do not lend themselves to clinical application at the bedside of patients undergoing emergency general surgery (EGS). Our aim was to develop a simplified risk calculator for prediction of early postoperative mortality following EGS. Study Design: EGS cases other than appendectomy and cholecystectomy were identified within the American College of Surgeons National Surgery Quality Improvement Program (ACS-NSQIP) database from 2005-2014. Seventy-five percent of the cases were selected at random for model development while 25% of the cases were used for model testing. Stepwise logistic regression was performed for creation of a 30-day mortality risk calculator. Model accuracy and reproducibility was investigated using the concordance index (c-statistic) and Pearson correlations. Results: A total of 79,835 patients met inclusion criteria. Overall 30-day mortality was 12.6%. A simplified risk model formula was derived from five readily available preoperative variables as follows: 0.034*Age+ 0.8*Non-Independent Status + 0.88*Sepsis + 1.1 (if BUN > 29) or 0.57 (if BUN >18 and 2.7 and

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