Association between blood urea nitrogen and 30-day mortality in patients with sepsis: a retrospective analysis

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Abstract

Background: Patients with sepsis have a high mortality rate. Rapid and effective risk stratification indicators for sepsis-related death are urgently needed to explored. Blood urea nitrogen (BUN) level can reflect the protein catabolism in the human body and the degree of renal impairment. So it has particular value for the management of septic patients. In this study, we explored the relationship between BUN level and 30-day mortality in patients with sepsis. Methods: In this retrospective cohort study, a total of 12,713 patients with sepsis from the Medical Information Mart for Intensive Care III (MIMIC-III) database were included. BUN level at admission was retrieved, and the outcome indicator was the 30-day mortality. Multivariate Cox regression analysis and smoothed curve fitting were used to assess the relationship between BUN and 30-day mortality. Results: A total of 12,713 patients with sepsis were screened. The overall 30-day mortality rate was 20.6%. The multivariate Cox regression model and smoothed curve fitting revealed a nonlinear association between BUN and 30-day mortality. The inflection point occurred at 41.1 mg/dL. The effect size was 1.298 on the left side of the inflection point [hazard ratio (HR) =1.298; 95% confidence interval (CI): 1.224–1.376; P<0.001] and 1.045 on the right side of the inflection point (HR =1.045; 95% CI: 1.016–1.075; P=0.002). Conclusions: There is a nonlinear correlation between BUN and 30-day mortality in patients with sepsis. With 41.1 mg/dL as a cutoff level for BUN, patients have a remarkably different risk of death and should be managed differently.

References Powered by Scopus

The third international consensus definitions for sepsis and septic shock (sepsis-3)

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CITATION STYLE

APA

Li, X., Zheng, R., Zhang, T., Zeng, Z., Li, H., & Liu, J. (2021). Association between blood urea nitrogen and 30-day mortality in patients with sepsis: a retrospective analysis. Annals of Palliative Medicine, 10(11), 11653–11663. https://doi.org/10.21037/apm-21-2937

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