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. 2025 May 7:12:1510919.
doi: 10.3389/fmed.2025.1510919. eCollection 2025.

Prognostic value of blood urea nitrogen to albumin ratio in septic patients with acute kidney injury-a retrospective study based on MIMIC database

Kun Han  1 , Yuxia Tao  1 , Jianhao Wang  1   2 , Jinshuai Lu  2
Affiliations

Prognostic value of blood urea nitrogen to albumin ratio in septic patients with acute kidney injury-a retrospective study based on MIMIC database

Kun Han et al. Front Med (Lausanne). .

Abstract

Objective: To investigate the predictive value of blood urea nitrogen to albumin ratio (BAR) in the prognosis of patients with sepsis-induced acute kidney injury (S-AKI).

Methods: A retrospective analysis was conducted on patient data from the MIMIC-IV database that met the S-AKI criteria. Cox regression was employed to analyze the relationship between BAR and 28-day mortality risk. BAR was divided into four quartiles (Q1, Q2, Q3, Q4), and Kaplan-Meier survival analysis was performed to compare the 28-day cumulative survival rates among the four patient groups. Simultaneously, the log-rank test was used for statistical analysis of survival rate differences among the four groups. Subsequently, Cox regression was performed with Q1 (the lowest quartile) as the reference for comparison. Restricted cubic splines (RCS) were utilized to analyze the non-linear association between BAR and mortality risk, with the median BAR of all patients serving as the reference point to define the non-linear effect. Thereafter, correlation analysis and subgroup analysis were conducted to assess the stability of BAR in predicting 28-day prognosis. LASSO regression analysis was applied to select variables related to 28-day prognosis, and relevant variables were screened through univariate and multivariate logistic regression analyses to construct a nomogram model. The area under the receiver operating characteristic curve (AUC), calibration plot, and decision curve analysis (DCA) were used to evaluate the predictive performance of the nomogram for in-hospital mortality in S-AKI patients.

Results: A total of 8,666 patients with S-AKI were included, among whom 2,396 died (27.65%). Cox analysis of BAR indicated a positive correlation between BAR and 28-day mortality risk, with an HR of 1.029 (95% CI: 1.026-1.032). Kaplan-Meier curves showed that the 28-day cumulative survival rate was significantly lower in the Q4 group compared to the Q1 group of S-AKI patients (log-rank test, χ2 = 381.5, p < 0.001). Subsequently, Cox regression with Q1 as the reference revealed that the risk of death gradually increased with ascending BAR quartiles (Q4 vs. Q1: HR = 0.639, 95% CI: 0.579-0.705, P < 0.001). Correlation analysis suggested no significant correlation between BAR and other biological indicators. Additionally, subgroup analysis confirmed the stability of the results. The ROC curve demonstrated that BAR had diagnostic advantages over single indicators such as blood urea nitrogen or albumin (p < 0.001; p < 0.001). A nomogram incorporating multiple factors including BAR was constructed, which outperformed SOFA and SAPS II in predicting in-hospital mortality for S-AKI, demonstrating good discrimination and calibration capabilities.

Conclusion: BAR, as a simple and convenient biomarker, can effectively predict in-hospital mortality in patients with S-AKI, with its elevation positively correlated with an increased risk of death. The rise in BAR is positively associated with an increased 28-day mortality risk in S-AKI patients, and a higher absolute value of BAR indicates a poorer prognosis for S-AKI patients. The nomogram incorporating BAR demonstrates excellent performance in prediction.

Keywords: blood urea nitrogen to albumin ratio; mortality rate; nomogram; sepsis; sepsis-induced acute kidney injury.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
The flowchart of patients screening.
FIGURE 2
FIGURE 2
The Kaplan-Meier survival curves were used to compare the 28-day cumulative survival rates of BAR in the Q1, Q2, Q3, and Q4 groups.
FIGURE 3
FIGURE 3
RCS analysis of the relationship between BAR and the risk of 28-day all-cause mortality in S-AKI patients. The shaded area represents the 95% confidence interval.
FIGURE 4
FIGURE 4
The predictive value of ALB, BUN and BAR for the prognosis of S-AKI in critically ill patients was compared.
FIGURE 5
FIGURE 5
The predictive value of BAR for 28-day mortality, ICU mortality and in-hospital mortality in critically ill patients with S-AKI was compared.
FIGURE 6
FIGURE 6
Correlation analysis heatmap.
FIGURE 7
FIGURE 7
The subgroup analysis between BAR and 28-day all-cause mortality.
FIGURE 8
FIGURE 8
(A) Selection process of prognostic variables of S-AKI by LASSO regression. (B) Selection process of the value of lambda by cross validation.
FIGURE 9
FIGURE 9
The survival nomogram for predicting in-hospital mortality of S-AKI patients. When using it, drawing a vertical line from each variable upward to the points and then recording the corresponding points. The point of each variable was then summed up to obtain a total score that corresponds to a predicted probability of in-hospital mortality at the bottom of the nomogram
FIGURE 10
FIGURE 10
(A) The calibration curve for predicting in-hospital mortality. (B) Receiver operating characteristic curve analysis of blood urea nitrogen to serum albumin ratio and nomogram for in-hospital mortality prediction. (C) Decision curve analysis DCA of the nomogram to predict in-hospital mortality.
FIGURE 11
FIGURE 11
The discrimination performance of the newly developed prediction model was compared with the nomogram model with BAR removed and SOFA and SAPS II.
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