Research Article: Correlation between blood urea nitrogen/albumin levels and 30-day all-cause mortality in critically Ill patients with heart failure: a retrospective cohort study and predictive model development based on machine learning
Abstract:
The aim of this study was to investigate the correlation between blood urea nitrogen-albumin index (BAR) and 30-day and one-year all-cause mortality in patients with heart failure admitted to the intensive care unit (ICU).
This is a retrospective cohort study with data from two non-overlapping datasets from the Medical Information Marketplace in Intensive Care (MIMIC), where MIMIC-IV was used for training and MIMIC-III for external validation. Risk ratios (HR) and 95% confidence intervals (CI) between the BAR index and all-cause mortality were assessed using Cox proportional risk regression and Kaplan–Meier curves. Restricted cubic spline regression modeling was used to assess potential nonlinear relationships between BAR indices and outcome indicators. Nine machine learning (ML) algorithms were used to build predictive models, and, in addition, the Shapley additive interpretation (SHAP) method was used to determine feature importance.
This study included 2,470 critically ill heart failure patients. Multivariate Cox regression analysis revealed that the risk of all-cause mortality was significantly higher at both 30 and 365 days for patients in the highest quartile of the BAR index. Kaplan–Meier analyses indicated that the cumulative incidence of mortality increased with higher quartiles of the BAR ratio. Additionally, multivariate restricted cubic spline regression showed a nonlinear increase in death risk at 30 and 365 days with higher BAR index values. Subgroup analyses confirmed consistent effect sizes and stability across groups. Among the nine models, XGBoost performs the best, with an AUC value of 0.894 [95% confidence interval (CI): 0.85–0.93] in the internal validation dataset and 0.924 [95% confidence interval (CI): 0.88–0.96]. The model demonstrated the best predictive performance in terms of discrimination and clinical application.
We found that higher BAR levels were significantly associated with a higher risk of 30- and 365-day all-cause mortality in critically ill patients with heart failure.
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