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P121: Derivation of a clinical decision tool for predicting adverse outcomes among emergency department patients with lower gastrointestinal bleeding

Published online by Cambridge University Press:  11 May 2018

R. Ramaekers*
Affiliation:
University of Ottawa, Department of Emergency Medicine, Ottawa, ON
C. Leafloor
Affiliation:
University of Ottawa, Department of Emergency Medicine, Ottawa, ON
J. J. Perry
Affiliation:
University of Ottawa, Department of Emergency Medicine, Ottawa, ON
V. Thiruganasambandamoorthy
Affiliation:
University of Ottawa, Department of Emergency Medicine, Ottawa, ON
*
*Corresponding author

Abstract

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Introduction: Lower gastrointestinal bleeding (LGIB) can result in serious adverse events, including recurrent bleeding, need for intervention and death. Endoscopy is important in the management of LGIB, however gastroenterologists have limited resources to safe endoscopy. Risk stratification of LGIB patients can aid physicians in disposition decisions. Objective: to develop a clinical decision tool to accurately identify LGIB patients presenting to the emergency department (ED) who are at risk for 30-day serious adverse events. Methods: We conducted a health records review and included 372 adult ED patients who presented with an acute LGIB. The outcome was a 30-day composite outcome consisting of all-cause death, recurrent LGIB, need for intervention to control the bleed and ICU admission. A second researcher confirmed data-collection of 10% of the data and we calculated a -value for inter-rater reliability. We analyzed the data using stepwise backwards selection and SELECTION=SCORE option and calculated the diagnostic accuracy of the final model. Results: Age 75 years, hemoglobin 100 g/L, INR 2.0, a bloody stool in the ED and a past medical history of colorectal polyps were significant predictors in the multivariable regression analysis. The AUC was 0.83 (95% CI 0.77-0.89), sensitivity 0.96 (0.90-1.00), specificity 0.53 (0.48-0.59), and negative likelihood ratio 0.08 (0.02-0.30) for a cut-off score of 1. Conclusion: This model showed good ability to identify LGIB patients at low risk for adverse events as evidenced by the high AUC, sensitivity and negative likelihood ratio. Future, large prospective studies should be done to confirm the data, after which it should be validated and implemented.

Type
Poster Presentations
Copyright
Copyright © Canadian Association of Emergency Physicians 2018