The red cell distribution width to albumin ratio as a novel biomarker for predicting short-term mortality in severe pulmonary sepsis: a retrospective study with dual-cohort validation

Background: The Red Cell Distribution Width to Albumin Ratio (RAR) is a biomarker that reflects a patient's nutritional status, inflammatory response, and oxidative stress, showing significant potential in critical care medicine. To investigate its prognostic value, we conducted a retrospective study using a dual-cohort design to assess the association between RAR and short-term (28-day) mortality in patients with pulmonary sepsis. Materials and methods: We retrospectively identified patients with sepsis secondary to pulmonary infections from the Binzhou Medical University Hospital medical records and the Medical Information Mart for Intensive Care (MIMIC-IV) database. To examine the association between RAR and short-term adverse outcomes in these patients, we employed several statistical methods, including Kaplan-Meier survival curves, multivariable Cox regression, and restricted cubic spline (RCS) analysis. Subsequently, we applied machine learning algorithms-namely the Boruta algorithm, LASSO-COX regression, and Random Forests-to identify the most predictive features. These features were then used to develop a final multivariable Cox regression model for risk prediction. The performance of this predictive model was evaluated using receiver operating characteristic (ROC) curve analysis. Result: The final analysis included 6,065 patients with pulmonary sepsis. The 28-day ICU and in-hospital mortality rates were 20.50 and 19.30%, respectively. In the fully adjusted multivariable model, a higher RAR was significantly associated with increased 28-day ICU and in-hospital mortality, whether treated as a continuous or categorical variable. For each unit increase in the continuous RAR score, the hazard ratios (HR) for 28-day ICU and in-hospital mortality were 1.52 (95% CI: 1.28-1.80) and 1.30 (95% CI: 1.09-1.55), respectively. Similarly, when compared to the low RAR group, the high RAR group had hazard ratios of 1.45 (95% CI: 1.23-1.70) and 1.29 (95% CI: 1.09-1.52) for the two outcomes. The restricted cubic spline (RCS) analysis revealed a positive dose-response relationship between RAR levels and short-term adverse outcomes. Furthermore, the risk prediction model incorporating RAR and eight other independent predictors demonstrated superior performance in identifying high-risk patients compared to traditional critical illness scoring systems, as shown by receiver operating characteristic (ROC) analysis. All findings were consistently validated in the external cohort. Conclusion: In conclusion, our study demonstrates a significant inverse association between the RAR and short-term survival in patients with severe pulmonary sepsis. The RAR-based scoring system we developed shows promise as a practical adjunct tool for clinical risk assessment. Prospective validation is warranted to confirm its utility in improving risk stratification for this patient population.

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Journal
Frontiers in Medicine
Published
2026-04-07
DOI
https://doi.org/10.3389/fmed.2026.1805614
Primary Topic
Inflammatory Biomarkers in Disease Prognosis
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article

The red cell distribution width to albumin ratio as a novel biomarker for predicting short-term mortality in severe pulmonary sepsis: a retrospective study with dual-cohort validation

Shasha Wang, Han Gao, Tianyi Zhang
Frontiers in Medicine
Inflammatory Biomarkers in Disease Prognosis
article

The red cell distribution width to albumin ratio as a novel biomarker for predicting short-term mortality in severe pulmonary sepsis: a retrospective study with dual-cohort validation

Shasha Wang, Han Gao, Tianyi Zhang
article en

Abstract

Background: The Red Cell Distribution Width to Albumin Ratio (RAR) is a biomarker that reflects a patient's nutritional status, inflammatory response, and oxidative stress, showing significant potential in critical care medicine. To investigate its prognostic value, we conducted a retrospective study using a dual-cohort design to assess the association between RAR and short-term (28-day) mortality in patients with pulmonary sepsis. Materials and methods: We retrospectively identified patients with sepsis secondary to pulmonary infections from the Binzhou Medical University Hospital medical records and the Medical Information Mart for Intensive Care (MIMIC-IV) database. To examine the association between RAR and short-term adverse outcomes in these patients, we employed several statistical methods, including Kaplan-Meier survival curves, multivariable Cox regression, and restricted cubic spline (RCS) analysis. Subsequently, we applied machine learning algorithms-namely the Boruta algorithm, LASSO-COX regression, and Random Forests-to identify the most predictive features. These features were then used to develop a final multivariable Cox regression model for risk prediction. The performance of this predictive model was evaluated using receiver operating characteristic (ROC) curve analysis. Result: The final analysis included 6,065 patients with pulmonary sepsis. The 28-day ICU and in-hospital mortality rates were 20.50 and 19.30%, respectively. In the fully adjusted multivariable model, a higher RAR was significantly associated with increased 28-day ICU and in-hospital mortality, whether treated as a continuous or categorical variable. For each unit increase in the continuous RAR score, the hazard ratios (HR) for 28-day ICU and in-hospital mortality were 1.52 (95% CI: 1.28-1.80) and 1.30 (95% CI: 1.09-1.55), respectively. Similarly, when compared to the low RAR group, the high RAR group had hazard ratios of 1.45 (95% CI: 1.23-1.70) and 1.29 (95% CI: 1.09-1.52) for the two outcomes. The restricted cubic spline (RCS) analysis revealed a positive dose-response relationship between RAR levels and short-term adverse outcomes. Furthermore, the risk prediction model incorporating RAR and eight other independent predictors demonstrated superior performance in identifying high-risk patients compared to traditional critical illness scoring systems, as shown by receiver operating characteristic (ROC) analysis. All findings were consistently validated in the external cohort. Conclusion: In conclusion, our study demonstrates a significant inverse association between the RAR and short-term survival in patients with severe pulmonary sepsis. The RAR-based scoring system we developed shows promise as a practical adjunct tool for clinical risk assessment. Prospective validation is warranted to confirm its utility in improving risk stratification for this patient population.

Frontiers in MedicineVol. 13
Shandong University of Aeronautics (CN), Binzhou Medical College Hospital (CN)
Zero hunger
Openalex Percentile: Top 30%
Inflammatory Biomarkers in Disease Prognosis
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