Risk stratification in acute upper GI bleeding: comparison of the AIMS65 score with the Glasgow-Blatchford and Rockall scoring systems

Abstract

The American College of Gastroenterology recommends early risk stratification in patients presenting with upper GI bleeding (UGIB). The AIMS65 score is a risk stratification score previously validated to predict inpatient mortality. The aim of this study was to validate the AIMS65 score as a predictor of inpatient mortality in patients with acute UGIB and to compare it with established pre- and postendoscopy risk scores. ICD-10 (International Classification of Diseases, Tenth Revision) codes identified patients presenting with UGIB requiring endoscopy. All patients were risk stratified by using the AIMS65, Glasgow-Blatchford score (GBS), pre-endoscopy Rockall, and full Rockall scores. The primary outcome was inpatient mortality. Secondary outcomes were a composite endpoint of inpatient mortality, rebleeding, and endoscopic, radiologic, or surgical intervention; blood transfusion requirement; intensive care unit (ICU) admission; rebleeding; and hospital length of stay. The area under the receiver-operating characteristic curve (AUROC) was calculated for each score. Of the 424 study patients, 18 (4.2%) died and 69 (16%) achieved the composite endpoint. The AIMS65 score was superior to both the GBS (AUROC, 0.80 vs 0.76, P< .027) and the pre-endoscopy Rockall score (0.74, P= .001) and equivalent to the full Rockall score (0.78, P= .18) in predicting inpatient mortality. The AIMS65 score was superior to all other scores in predicting the need for ICU admission and length of hospital stay. AIMS65, GBS, and full Rockall scores were equivalent (AUROCs, 0.63 vs 0.62 vs 0.63, respectively) and superior to pre-endoscopy Rockall (AUROC, 0.55) in predicting the composite endpoint. GBS was superior to all other scores for predicting blood transfusion. The AIMS65 score is a simple risk stratification score for UGIB with accuracy superior to that of GBS and pre-endoscopy Rockall scores in predicting in-hospital mortality and the need for ICU admission.