Natalie Tapaskar1, Blake Jones1, Steve Mei2, Neil Sengupta2. 1. Department of Medicine, The University of Chicago Medical Center, Chicago, Illinois, USA. 2. Section of Gastroenterology, Hepatology & Nutrition, The University of Chicago Medical Center, Chicago, Illinois, USA.
Abstract
BACKGROUND AND AIMS: Limited data exist on prediction of adverse outcomes in patients with acute lower GI bleeding (LGIB). The purpose of our study was to compare the ability of existing validated clinical risk scores to predict relevant outcomes in LGIB. METHODS: We performed a prospective observational study of patients admitted with LGIB who underwent colonoscopy at a single center between April 2016 and September 2017. Seven risk scores were calculated at admission (Strate, NOBLADS, Sengupta, Oakland, Blatchford, AIMS65, and Charlson Comorbidity Index). The risk of severe LGIB was determined via univariable and multivariable logistic regression. Area under the receiver operating characteristic curve (AUC) analysis was used to compare the scores. RESULTS: We included 170 patients admitted with LGIB requiring colonoscopy. Fifty-two percent (n = 89) fit criteria for severe bleeding. Patients with severe bleeding had lower admission hemoglobin levels (8.6 g/dL vs 11.1 g/dL; P = .0001), were more likely to have blood transfusions (85% vs 36%; P < .0001), intensive care unit stays (49% vs 19%; P < .0001), and had a longer length of stay (6 days vs 4 days; P = .0009). The Oakland score was best for prediction of severe bleeding (AUC, .74), Blatchford score for blood transfusion (AUC, .87), and Strate score for in-hospital recurrent bleeding (AUC, .66) and endoscopic intervention (AUC, .62). The strongest individual predictors of severe bleeding were low admission hemoglobin (odds ratio, 1.28 per 1-g/dL decrease; P = .0015; 95% confidence interval, 1.10-1.49) and low albumin (odds ratio, 2.56 per 1-g/dL decrease; P = .02; 95% confidence interval, 1.16-5.56). CONCLUSION: Admission albumin and hemoglobin levels were the strongest predictors of severe bleeding. No singular clinical risk tool had the best predictive ability across all outcomes.
BACKGROUND AND AIMS: Limited data exist on prediction of adverse outcomes in patients with acute lower GI bleeding (LGIB). The purpose of our study was to compare the ability of existing validated clinical risk scores to predict relevant outcomes in LGIB. METHODS: We performed a prospective observational study of patients admitted with LGIB who underwent colonoscopy at a single center between April 2016 and September 2017. Seven risk scores were calculated at admission (Strate, NOBLADS, Sengupta, Oakland, Blatchford, AIMS65, and Charlson Comorbidity Index). The risk of severe LGIB was determined via univariable and multivariable logistic regression. Area under the receiver operating characteristic curve (AUC) analysis was used to compare the scores. RESULTS: We included 170 patients admitted with LGIB requiring colonoscopy. Fifty-two percent (n = 89) fit criteria for severe bleeding. Patients with severe bleeding had lower admission hemoglobin levels (8.6 g/dL vs 11.1 g/dL; P = .0001), were more likely to have blood transfusions (85% vs 36%; P < .0001), intensive care unit stays (49% vs 19%; P < .0001), and had a longer length of stay (6 days vs 4 days; P = .0009). The Oakland score was best for prediction of severe bleeding (AUC, .74), Blatchford score for blood transfusion (AUC, .87), and Strate score for in-hospital recurrent bleeding (AUC, .66) and endoscopic intervention (AUC, .62). The strongest individual predictors of severe bleeding were low admission hemoglobin (odds ratio, 1.28 per 1-g/dL decrease; P = .0015; 95% confidence interval, 1.10-1.49) and low albumin (odds ratio, 2.56 per 1-g/dL decrease; P = .02; 95% confidence interval, 1.16-5.56). CONCLUSION: Admission albumin and hemoglobin levels were the strongest predictors of severe bleeding. No singular clinical risk tool had the best predictive ability across all outcomes.
Authors: Samuel C L Smith; Alina Bazarova; Efe Ejenavi; Maria Qurashi; Uday N Shivaji; Phil R Harvey; Emma Slaney; Michael McFarlane; Graham Baker; Mohamed Elnagar; Sarah Yuzari; Georgios Gkoutos; Subrata Ghosh; Marietta Iacucci Journal: Int J Colorectal Dis Date: 2019-12-16 Impact factor: 2.571
Authors: Kathryn Oakland; Sandeepkumar Kothiwale; Tyler Forehand; Edmund Jackson; Cliff Bucknall; Michael S L Sey; Siddharth Singh; Vipul Jairath; Jonathan Perlin Journal: JAMA Netw Open Date: 2020-07-01