Association Between Red Cell Distribution Width and Liver Injury after Cardiac and Aortic Aneurysm Surgery with Cardiopulmonary Bypass

Objectives: This study aimed to investigate the association between preoperative red blood cell distribution width (RDW) levels and liver injury (LI) after cardiac surgery, to highlight RDW's usefulness in the early identification and intervention for patients at high risk of LI. Design: A retrospective observational study. Setting: A university-affiliated teaching hospital and tertiary referral center. Participants: Adult patients who underwent cardiac and aortic aneurysm surgery at Changhai Hospital in 2021. Interventions: Postoperative LI was defined by increased liver enzyme levels and/or hyperbilirubinemia, noted from the time of surgery to discharge. Logistic regression analyses were conducted to examine the RDW-LI relationship, with stratified analyses based on age, gender, and anemia. Survival within 30 days was assessed using the Kaplan-Meier method, with survival curve differences analyzed via the log-rank test. The study included 3 sets of sensitivity analyses. Measurements and Main Results: Postoperative LI was observed in 75 patients (10%). Multivariate regression analysis showed a significant association between high RDW levels and postoperative LI (adjusted odds ratio, 3.25; p = 0.033; 95% confidence intefal, 1.10-9.63), even after adjusting for all covariates. This association remained consistent across 3 sets of sensitivity analyses. Subgroup analysis showed men had a higher correlation with LI (p for interaction = 0.041). Kaplan-Meier analysis indicated a significantly lower survival rate in the LI group (76%) compared with the non-LI group (99.6%; p < 0.001). Conclusions: Preoperative RDW levels are significantly associated with postoperative LI. RDW could serve as a significant useful marker for early detection and intervention in patients at high risk of LI, thereby potentially improving patient outcomes. (c) 2024 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.