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Updated: Aug 15, 2025

Author Spotlight: A Multi-Depth Porcine Model for Comprehensive Study of Burn Injuries and Healing Processes
Published on: February 23, 2024
An Increase in Admission RDW Value Is Associated with Excess Short-Term Mortality Rates in Patients with Severe Burns
Honghao Lai1,2, Zhuhong Cai3, Shengyong Wu4
1Department of Burn, Changhai Hospital, Naval Medical University, Shanghai, 200433, China.
Abstract:
The predictive value of red blood cell distribution width (RDW) in severely burned patients remains unclear. This study aimed to investigate the potential association between admission RDW and outcomes in patients with severe burns. Data of severely burned patients in the burn center of Changhai Hospital were retrospectively evaluated. The relationship between admission RDW and mortality was analyzed and displayed using the receiver operating characteristic curve, Kaplan-Meier curve, Cox proportional hazards regression, and the nomogram method. A total of 342 patients were identified according to the filter criteria. The 30-day mortality was 12.9%, and the mortality rates in 7 days and 90 days were 2.9% and 16.7%, respectively. Patients with high admission RDW value were more likely to die than those with low RDW value. Multivariate analysis revealed that higher admission RDW, age, full-thickness burned area, and inhalation injury were independent risk factors with 30-day mortality. The nomogram based on these risk factors was established to predict survival probability in severe burn patients. The C-index of different follow-up times was computed between 0.867 and 0.904, and the nomogram model list fits the data well. Admission RDW played a valuable role in predicting short-term mortality in patients with severe burns. The nomogram containing admission RDW was established to predict mortality, which helps burn care providers identify the patients at higher risk of short-term mortality after severe burns. More attention should be paid to the application of these easy and inexpensive biochemical indicators in the early prediction of disease progression.
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