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Multicenter Study
. 2025 May 31;184(6):377.
doi: 10.1007/s00431-025-06162-0.

Risk factors associated with persistent coronary artery lesions in children with Kawasaki disease in an Italian cohort

Affiliations
Multicenter Study

Risk factors associated with persistent coronary artery lesions in children with Kawasaki disease in an Italian cohort

Fiorentina Guida et al. Eur J Pediatr. .

Abstract

Kawasaki disease (KD) can be complicated-particularly during the acute phase-by coronary artery lesions (CALs). The persistence of CALs (pCALs) beyond the subacute phase increases the risk of long-term cardiovascular morbidity and life-threatening events. While several risk scores, primarily based on Asian and American populations, have been proposed to predict CALs or treatment resistance, few studies have focused on identifying risk factors for pCALs. This study aimed to identify risk factors for pCALs in Italian patients and to evaluate the validity of an existing risk score developed in a North American cohort. Data from KD patients across 11 Italian centers were collected in a centralized RedCap database. pCALs were defined as CALs persisting 8 weeks post-diagnosis. Clinical, demographic, and laboratory features of patients with and without pCALs were compared. Independent risk factors were identified using multiple logistic regression. The predictive performance of Son's risk score was assessed through ROC analysis. A total of 517 children (87.4% Caucasian) were enrolled; 52 developed pCALs. pCALs were more common in males (12.03%, p = 0.06), patients < 6 months (61.5%, p = 0.05), those with Asian ethnicity (26.9%, p = 0.026), incomplete clinical presentation (p = 0.03), and in those with abnormal abdominal ultrasound findings (p = 0.04). Affected children had higher WBC, elevated CRP (> 13 mg/dL), and lower hemoglobin. Compared to those with acute CALs, patients with pCALs were younger, more often IVIG non-responders (34.6% vs. 29.6%, p < 0.001), and late-treated. Son's score showed good predictive ability for pCALs.Conclusions: Male sex, younger age, incomplete presentation, Asian ethnicity, and elevated CRP are independent risk factors for pCALs in Italian children with KD. Son's score may help identify high-risk patients who could benefit from closer follow-up and early adjunctive therapy, even in predominantly Caucasian populations. What is Known: • Kawasaki disease can cause CALs, which increase cardiovascular risk if they persist • Previous research has focused mainly on predicting CALs or treatment resistance, but little evidence is available on the risk factors for CALs persistence What is New: • Our study identifies independent risk factors for pCALs in Italian children: male gender, younger age, incomplete presentation, Asian ethnicity, and high CRP levels • By applying the Son Risk Score to our population, we confirmed its predictive value in a predominantly Caucasian cohort and its reliability in identifying susceptibility to CALs persistence.

Keywords: Coronary artery aneurysms; Kawasaki disease; Persistent coronary artery lesions; Risk factors; Risk score.

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Conflict of interest statement

Declarations. Ethics approval: This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of IRCCS AOU BO (Avec 340/2017/O/OssAOUBO approved on 1/16/2019). Informed consent: Informed consent was obtained from all individual participants included in the study. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
The application of Son’s risk score to predict the development of pCALs in the presented population. The ROC curve evaluates the performance of Son’s risk prediction model (35) in predicting the development of pCALs. The X-axis represents the false positive rate (1—Specificity), and the Y-axis represents the true positive rate (Sensitivity). The blue curve illustrates the model’s ability to distinguish between positive and negative classes at various threshold settings. The green diagonal line signifies random classification. The area under the ROC curve (AUC) is 0.7915, indicating that the model has good discriminative power

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