Abstract 13230: Prediction of Coronary Artery Lesions Caused by Treatment-Resistant Kawasaki Disease Before Initial Treatment

Abstract

Introduction: Kawasaki disease (KD), which is the most common multisystem vasculitis with unknown causes in childhood, causes coronary artery lesions (CALs). Especially in the case of treatment resistance, CALs occur at a high rate. To prevent CALs, it is important to identify risks as early as possible and establish aggressive treatment strategies. Hypothesis: CALs caused by treatment-resistant KD cases can be predicted before initial treatment. Methods: Fifty-five KD patients who scored high in all three Japanese Intravenous immunoglobulin (IVIG) non-response prediction scoring systems were included. We detected independent risk factors that contribute to the prediction of CALs due to treatment-resistant KD by multivariate analysis, determined the cut-off value for identifying subjects at risk of CALs by receiver operating characteristic analysis, and developed a new model for predicting CALs (including transient dilatation) due to treatment-resistant KD. Results: Neutrophils and Total bilirubin (T-bil) before initial treatment were detected as independent risk factors. When both neutrophils >20,000 and T-bil >2.5 were present (high-risk group), CALs occurred with a sensitivity of 100%, a specificity of 96%, a positive predictive value of 71%, and a negative predictive value of 100%. There were five patients out of seven who had coronary artery dilation greater than z-score >2.5 by treatment resistance, compared to zero patients out of forty-eight in low-risk group (p<0.01). Conclusions: It may be possible to predict CALs caused by treatment-resistant KD cases with high sensitivity and specificity before initial treatment with a new model using neutrophils and T-bil. If the occurrence of CALs due to treatment-resistant KD is expected, it is possible to consider an aggressive treatment strategy from the initial treatment.