The role of the Lactate-to-Albumin ratio in predicting ICU admission and mortality in patients with UGIB presenting to the ED: a prospective observational study

Abstract

Background: Upper gastrointestinal bleeding (UGIB) remains a common and potentially life-threatening condition frequently encountered in emergency departments (EDs). Early risk stratification tools are essential for predicting outcomes such as intensive care unit (ICU) admission and in-hospital mortality.

Objectives: To evaluate the predictive performance of the serum lactate-to-albumin ratio (LAR) for ICU admission and in-hospital mortality in patients presenting to the ED with UGIB.

Methods: This prospective observational study included 181 patients who presented to a university hospital ED with UGIB. Demographic characteristics, laboratory parameters, medication use, and clinical outcomes were recorded. The diagnostic performance of LAR, blood urea nitrogen (BUN) -to-albumin ratio (BAR), and AIMS65 scores for ICU admission and mortality was assessed using ROC analysis and multivariate logistic regression.

Results: LAR was significantly elevated in patients requiring ICU admission (p < 0.001). LAR showed a similar predictive value to AIM65 and a superior predictive value to BAR for both ICU admission and in-hospital mortality, compared to BAR and AIM65. The area under the curve (AUC) for LAR was 0.789 for ICU admission and 0.858 for mortality. Multivariate analysis identified LAR, underlying liver disease, and high AIMS65 score as independent predictors of in-hospital mortality.

Conclusion: The lactate-to-albumin ratio is a simple, readily available, and effective biomarker for predicting adverse outcomes in UGIB patients. It may serve as a rapid and practical decision-making tool in emergency settings, complementing or potentially replacing existing scoring systems.

Clinical trial number: not applicable.

Keywords: Emergency department; Intensive care; Lactate-to-albumin ratio; Mortality; Upper gastrointestinal bleeding.

Fig. 1

Study flowchart

Fig. 2

ROC curves demonstrating AUC values for prediction of ICU admission

Fig. 3

ROC Curves and AUC values for predicting in-hospital mortality

Fig. 4

Forest plot of multivariate logistic regression analysis for ICU Admission. Horizontal axis: odds ratio, odds ratios (points), and 95% CI (whiskers)

Fig. 5

Forest plot of multivariate logistic regression analysis for In-Hospital Mortality. Horizontal axis: odds ratio, odds ratios (points), and 95% CI (whiskers)