A single postoperative red cell distribution width measurement predicts short- and long-term mortality in surgical patients

术后单次红细胞分布宽度测量即可预测手术患者的短期和长期死亡率。

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Abstract

BACKGROUND: The red cell distribution width (RDW) measures erythrocyte size variability and is linked to increased mortality in various diseases, including cardiovascular, kidney, and liver conditions. In critically ill patients, particularly those with sepsis, RDW is a prognostic marker. While its role in cardiac surgery patients is well established, its value in surgical patients is less well explored. This study investigates whether a single postoperative RDW measurement predicts short- and long-term mortality surgical intensive care unit (ICU) patients. METHODS: This retrospective cohort study analyzed data from 2312 surgery patients admitted to a surgical ICU over 2 years. The RDW was measured within 2 h of surgery and analyzed as a continuous and binary variable (threshold 15). Mortality at 30 days and 1 year was assessed using univariable and multivariable logistic regression and Cox regression models, adjusting for factors like the simplified acute physiology score 3 (SAPS3), lactate levels, age, sex, and comorbidities. Interaction analyses evaluated the impact of cofactor on RDW's mortality prediction. RESULTS: Of 2312 patients, 1687 (73.0%) had RDW < 15 and 625 (27.0%) had RDW ≥ 15. The RDW ≥ 15 patients were older (p < 0.001), had higher SAPS3 (p < 0.001), and more comorbidities. Elevated RDW was independently associated with increased 30-day and 1‑year mortality. In univariable analysis, each unit increase in RDW was linked to higher 30-day mortality (HR 1.169, 95% CI 1.110-1.230; p < 0.001) and 1‑year mortality (HR 1.153, 95% CI 1.122-1.186; p < 0.001). Moreover, RDW ≥ 15 significantly increased the risk of 30-day (HR [Hazard Ratio] 3.247, 95% CI 2.352-4.482; p < 0.001) and 1‑year mortality (HR 3.278, 95% CI 2.654-4.048; p < 0.001). Interaction analyses showed that lactate levels and pre-existing lung diseases influenced RDW's mortality prediction. Including RDW in multivariable models improved predictive accuracy, as indicated by the Akaike information criterion. CONCLUSION: Postoperative RDW is a reliable and cost-effective marker for predicting short- and long-term mortality in surgical patients. An RDW threshold of 15 identifies high-risk patients who may benefit from targeted follow-up, thus potentially improving outcomes. In summary, RDW enhances postoperative risk stratification and management.

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