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ORIGINAL RESEARCH article
Front. Cardiovasc. Med.
Sec. Pediatric Cardiology
Volume 12 - 2025 | doi: 10.3389/fcvm.2025.1532768
This article is part of the Research Topic Artificial Intelligence and Machine Learning in Pediatric Cardiology View all 6 articles
A Universal Model for Predicting Coronary Artery Lesions in Subgroups of Kawasaki Disease in China: Based on Cluster Analysis
Provisionally accepted- Kunming Children's Hospital, Kunming, China
Objective: Coronary artery lesions (CAL) represent the most severe complication of Kawasaki disease (KD). Currently, there is no standardized method for predicting CAL in KD, and the predictive effectiveness varies among different KD patients. Therefore, our study aims to establish distinct predictive models for CAL complications based on the characteristics of different clusters. Methods: We employed principal component clustering analysis to categorize 1,795 KD patients into different clustered subgroups. We summarized the characteristics of each cluster and compared the occurrence of CAL components within each cluster. Additionally, we utilized LASSO analysis to further screen for factors associated with CAL. We then constructed CAL predictive models for each subgroup using the selected factors and conducted preliminary validation and assessment. Results: Through PCA analysis, we identified three clusters in KD. We developed predictive models for each of the three clusters. The AUCs of the three predictive models were 0.789 (95% CI: 0.732-0.845), 0.894 (95% CI: 0.856-0.932), and 0.773 (95% CI: 0.727-0.819), respectively, all demonstrating good predictive performance. Conclusion: Our study identified the existence of three clusters among KD patients. We developed KD-related CAL predictive models with good predictive performance for each cluster with distinct characteristics. This provides reference for individualized precision treatment of KD patients and aids in the health management of coronary arteries in KD.
Keywords: kawasaki disease, Cluster analysis, Coronary artery lesions, Cardiovascular Diseases, Children's diseases
Received: 22 Nov 2024; Accepted: 24 Feb 2025.
Copyright: © 2025 Gong, Li, Fu, Su, Zhang, Li, Liu and Deng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Xiaomei Liu, Kunming Children's Hospital, Kunming, China
Lili Deng, Kunming Children's Hospital, Kunming, China
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