Abstract
BACKGROUND: Kawasaki disease (KD) is an acute vasculitis that causes coronary artery lesions. This study aimed to identify risk factors for the early prediction of coronary artery disease (CAD) in KD. METHODS: We conducted a retrospective analysis of 175 Japanese children diagnosed with KD between January 2019 and March 2024. Univariate and multivariate logistic regression analyses were performed to identify predictors of CAD, and the diagnostic performance of various indicators was assessed using receiver operating characteristic (ROC) curves. The correlations between red blood cell distribution width (RDW) and iron-related anemia biomarkers were also evaluated. RESULTS: Of these, 77 with CAD were classified into the CAD group, while 98 without CAD were categorized as the non-CAD group. Patients in the CAD group were younger and had lower levels of hemoglobin (Hb), total protein, albumin, uric acid, and urea nitrogen, but a higher RDW coefficient of variation (RDW-CV) than the non-CAD group. Logistic regression analysis identified RDW-CV as an independent predictor of CAD. ROC curve analysis demonstrated moderate predictive performance for RDW-CV, with an area under the curve of 0.636 (sensitivity, 55.8%; specificity, 70.4%). Significant correlations were observed between RDW-CV and iron-related anemia biomarkers in the CAD group, but not in the non-CAD group. CONCLUSIONS: Iron dysregulation may be associated with CAD, and RDW-CV may aid in identifying patients who may develop CAD in KD. Our findings were consistent with previous studies in other Asian populations, supporting the utility of RDW-CV as a predictor of CAD in KD in populations with various ethnic backgrounds.