Original Article
Relation between changes in red blood cell distribution width after coronary artery bypass grafting and early postoperative morbidity
Abstract
Background: Red blood cell distribution width (RDW) is highly associated with various clinical states. In the present study, we aimed to determine the natures of associations between RDW changes and early adverse events after isolated coronary artery bypass grafting (CABG).
Methods: We retrospectively analyzed medical records of enrolled 117 patients. Patients were classified into two groups depending on early adverse events (No-event vs. Event). Delta RDW values were calculated (ΔRDW: Post-Peak RDW minus Pre-RDW). Patients were divided into tertiles based on ΔRDW. The ΔRDW cut-off point for an adverse event was determined by receiver operating characteristic curve analysis. In addition, logistic regression analysis was performed to identify independent factors of early adverse events.
Results: Thirty eight patients experienced 53 early adverse events. ΔRDW and ΔC-reactive protein were significantly higher in the Events group than in the No-event group. Incidences of early adverse events increased significantly between ΔRDW tertiles (P<0.001). The ROC curve of ΔRDW showed that a ΔRDW of ≥1.45 had a sensitivity of 71.1% and a specificity of 78.2% for predicting an early adverse event after CABG (P<0.001). Multivariable analysis showed ΔRDW (P=0.042) and length of ICU stay (P<0.001) independently predicted an adverse event.
Conclusions: ΔRDW was identified to be an independent predictor of early adverse events, and a ΔRDW cut-off of 1.45 was found to predict early adverse events after CABG. Careful monitoring of RDW trends after isolated CABG provides a simple, inexpensive and objective means of predicting early adverse events.
Methods: We retrospectively analyzed medical records of enrolled 117 patients. Patients were classified into two groups depending on early adverse events (No-event vs. Event). Delta RDW values were calculated (ΔRDW: Post-Peak RDW minus Pre-RDW). Patients were divided into tertiles based on ΔRDW. The ΔRDW cut-off point for an adverse event was determined by receiver operating characteristic curve analysis. In addition, logistic regression analysis was performed to identify independent factors of early adverse events.
Results: Thirty eight patients experienced 53 early adverse events. ΔRDW and ΔC-reactive protein were significantly higher in the Events group than in the No-event group. Incidences of early adverse events increased significantly between ΔRDW tertiles (P<0.001). The ROC curve of ΔRDW showed that a ΔRDW of ≥1.45 had a sensitivity of 71.1% and a specificity of 78.2% for predicting an early adverse event after CABG (P<0.001). Multivariable analysis showed ΔRDW (P=0.042) and length of ICU stay (P<0.001) independently predicted an adverse event.
Conclusions: ΔRDW was identified to be an independent predictor of early adverse events, and a ΔRDW cut-off of 1.45 was found to predict early adverse events after CABG. Careful monitoring of RDW trends after isolated CABG provides a simple, inexpensive and objective means of predicting early adverse events.
