Chandra, Graciela Natalia
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Blood urea nitrogen as outcome predictor in acute coronary syndrome: A systematic review and meta-analysis Chandra, Graciela Natalia; Hendrawan, Fandi; Prasetyo, Hersati
Heart Science Journal Vol. 7 No. 2 (2026): The Evolving Landscape of Heart Failure
Publisher : Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.hsj.2026.007.02.9

Abstract

BACKGROUND: Predicting outcomes in acute coronary syndrome (ACS) remains challenging, as established risk scores often require variables that are unavailable in low-resource healthcare settings. Blood urea nitrogen (BUN) has demonstrated prognostic value in predicting cardiovascular disease outcomes, such as heart failure and infective endocarditis. However, no meta-analysis has yet evaluated its predictive role in ACS. This study evaluated the prognostic utility of BUN for mortality and major adverse cardiac events (MACE) in ACS. METHODS: A systematic review and meta-analysis were conducted using literature from PubMed, Cochrane, and Web of Science. Risk of bias was assessed using the Risk Of Bias In Non-randomized Studies-of Exposures (ROBINS-E) tool. Pooled analysis of hazard ratios (HR) was calculated utilizing a random-effects model based on restricted maximum likelihood method. Subgroup analysis and meta-regression were performed. Sensitivity analysis was done using graphical display of study heterogeneity. RESULTS: Ten studies consisting of 7,238 participants were included. Elevated BUN was associated with heightened risk of MACE and mortality (HR: 1.05, 95% CI: 1.03–1.07, p=0.0011) and remained significant after excluding two outlier studies (HR: 1.04, 95% CI: 1.02–1.05, p=0.0002). Univariate meta-regression identified age, hypertension, and diabetes as potential covariates (p=0.112, 0.221, and 0.194). Multivariate analysis revealed no independent predictors. CONCLUSION: BUN may serve as a promising biomarker for predicting MACE and mortality in ACS, particularly in resource-limited settings. Further research is needed to compare its performance with established biomarkers or traditional scoring systems.