Blood Urea Nitrogen to Serum Albumin Ratio Independently Predicts Mortality in Critically Ill Patients With Acute Pulmonary Embolism.
Jihong FangBin XuPublished in: Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis (2021)
Acute pulmonary embolism (APE) is one of the prominent causes of death in patients with cardiovascular disease. Currently, reliable biomarkers to predict the prognosis of patients with APE are limited. The present study aimed to investigate the association of blood urea nitrogen to serum albumin (B/A) ratio and intensive care unit (ICU) mortality in critically ill patients with APE. A retrospective cohort study was performed using data extracted from a freely accessible critical care database (MIMIC-III). Adult (≥18 years) patients of first ICU admission with a primary diagnosis of APE in the database were enrolled in the study. The primary endpoint was the ICU mortality rate while the 28-day mortality after ICU admission was the secondary endpoint. The data of survivors and non-survivors were compared. A total of 1048 patients with APE were enrolled in this study, of which 131 patients died in ICU and 169 patients died within 28 days after ICU admission. The B/A ratio in the non-survivors group was significantly higher compared to the survivors group (P < 0.001). The multivariate analysis revealed that the B/A ratio was an independent predictor of ICU mortality (odds ratio [OR] 1.10, 95% CI 1.07-1.14, P < 0.001) and all-cause mortality within 28 days after ICU admission (hazard ratio [HR] 1.07, 95% CI 1.05-1.09, P < 0.001) in APE patients. The B/A ratio showed a greater area under the curve (AUC) of ICU mortality prediction (0.80; P < 0.001) than simplified acute physiology score II (SAPSII) (0.79), systemic inflammatory response syndrome score (SIRS) (0.62), acute physiology score III (APSIII) (0.76) and sequential organ failure assessment (SOFA) score (0.71). The B/A ratio could be a simple and useful prognostic tool to predict mortality in critically ill patients with APE.
Keyphrases
- intensive care unit
- pulmonary embolism
- end stage renal disease
- mechanical ventilation
- ejection fraction
- cardiovascular disease
- newly diagnosed
- chronic kidney disease
- emergency department
- inflammatory response
- cardiovascular events
- young adults
- prognostic factors
- peritoneal dialysis
- type diabetes
- liver failure
- risk factors
- electronic health record
- machine learning
- lipopolysaccharide induced
- acute respiratory distress syndrome
- deep learning
- artificial intelligence
- lps induced
- patient reported outcomes
- respiratory failure