A novel predictive model for Intensive Care Unit admission in Emergency Department patients with upper gastrointestinal bleeding

Abstract

Acute upper gastrointestinal bleeding (UGIB) is a critical emergency. Conventional scoring models for patients with UGIB have limitations; thus, more suitable tools for the Emergency Department are necessary. We aimed to develop a new model that can identify significant predictors of Intensive Care Unit (ICU) admission in Emergency Department patients with UGIB and to compare its predictive accuracy with that of existing models. We retrospectively analyzed data from patients with UGIB treated between January 2020 and July 2022 at the Emergency Department of a single tertiary medical center. Using multivariable logistic regression and the area under the receiver operating characteristic curve (AUROC), we developed a new model to predict the probability of ICU admission. Among 433 patients, multiple logistic regression analysis identified sex, systolic blood pressure, diastolic blood pressure, hemoglobin level, platelet count, alanine transaminase level, and prothrombin time as significant predictors of ICU admission. Our model demonstrated superior predictive accuracy with an AUROC of 0.8539 (95% confidence interval [CI]: 0.8078–0.8999), outperforming the Glasgow–Blatchford score and AIMS65 score, which had AUROCs of 0.7598 (95% CI: 0.7067–0.8130) and 0.6930 (95% CI: 0.6324–0.7537), respectively. We implemented this model in a user-friendly calculator for clinical use. We identified key predictors of ICU admission that are crucial for hemodynamic stabilization in patients with UGIB. Our model, combined with this probability calculator, will enhance clinical decision-making and patient care for UGIB in emergency settings.