Value of cystatin C for Kawasaki disease with coronary artery aneurysm.

BACKGROUND

Cardiovascular and kidney diseases are interconnected through shared biological mechanisms. However, research on renal function in Kawasaki disease (KD) remains insufficient. This study focused on coronary artery aneurysm (CAA), a severe cardiac consequence of KD, aiming to examine the predictive value of cystatin C (Cys C) and other common laboratory indicators before and after intravenous immunoglobulin (IVIG) treatment on KD with CAA.

METHODS

Based on patients' coronary status, 122 KD individuals were categorized in this retrospective analysis. After comparing the clinical and laboratory information of the patients with KD, multivariate logistic regression analysis was employed to identify independent risk factors for CAA development among them. Additionally, the predictive values of these parameters in CAA development of KD were assessed by receiver operating characteristic (ROC) curves.

RESULTS

In this study, 28 patients (23.0%, 28/122) had CAA, including 12 who had coronary artery regression (9.8%, 12/122). The parameters with P<0.10 in the difference analysis, namely polymorphous exanthem, changes in the extremities, plateletocrit and Cys C before IVIG, prealbumin >107.2 mg/L and prognostic nutritional index >54.7 after IVIG, were included in multivariate logistic regression analysis. Finally, binary logistic regression analysis identified the pre-IVIG Cys C [odds ratio, 10.183; 95% confidence interval (CI): 1.158-89.525] as an independent risk factor for developing CAA among KD patients. In addition, the 0.71 Cys C cut-off value sampled within five days had a 100% sensitivity and a 42.9% specificity (area under the ROC curve =0.752, 95% CI: 0.577-0.928, P=0.03).

CONCLUSIONS

Higher pre-IVIG Cys C levels may be associated with increased CAA risk, but further large-scale prospective studies are needed to confirm its predictive utility. Furthermore, Cys C acquired within five days of disease onset may theoretically provide better prediction power for the CAA development in KD.