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Journals
Biomedicines
Special Issues
Updates on Kawasaki Disease
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Updates on Kawasaki Disease

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Molecular and Translational Medicine".

Deadline for manuscript submissions: 31 October 2025 | Viewed by 218

Special Issue Editor

Dr. Eisuke Suganuma

E-Mail Website
Guest Editor
Saitama Children's Medical Center, Saitama, Japan
Interests: children

Special Issue Information

Dear Colleagues,

Kawasaki disease, first described by Dr. Tomisaku Kawasaki in 1967, is a febrile systemic vasculitis that primarily affects infants and young children. The development of coronary artery aneurysms, the most serious complication, can lead to acute coronary events such as myocardial infarction. Thanks to the development of acute treatments, the incidence of coronary sequelae in Japan remains at 2–3%, but the development of treatments aimed at eliminating all instances of coronary artery aneurysms is desirable. In recent years, according to a report by Burns et al., data-driven analysis has revealed that Kawasaki disease can be divided into four clusters, each with individual characteristics such as age at onset, response to treatment, and risk of coronary artery aneurysm. Based on these findings, we recognize that individualizing treatment methods for each cluster will be important in preventing future coronary artery aneurysm complications. We hope that this Special Issue will lead to future advances in the acute management and individualized treatment of Kawasaki disease.

Dr. Eisuke Suganuma
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomedicines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • coronary artery aneurysm
  • cluster
  • individualized treatment

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Published Papers (1 paper)

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Research

11 pages, 1984 KiB  
Article
Limited Performance of Machine Learning Models Developed Based on Demographic and Laboratory Data Obtained Before Primary Treatment to Predict Coronary Aneurysms
by Mi-Jin Kim, Gi-Beom Kim, Dongha Yang, Yeon-Jin Jang and Jeong-Jin Yu
Biomedicines 2025, 13(5), 1073; https://doi.org/10.3390/biomedicines13051073 - 29 Apr 2025
Abstract
Background/objectives: Kawasaki disease is the leading cause of acquired heart disease in children within developed countries. Although treatment with intravenous immunoglobulin (IVIG) significantly reduces the incidence of coronary artery aneurysm (CAA), the risk of it persists, affecting long-term patient outcomes. While intensified [...] Read more.
Background/objectives: Kawasaki disease is the leading cause of acquired heart disease in children within developed countries. Although treatment with intravenous immunoglobulin (IVIG) significantly reduces the incidence of coronary artery aneurysm (CAA), the risk of it persists, affecting long-term patient outcomes. While intensified primary treatment is recommended for patients at high risk of IVIG resistance or CAA development, a universally accepted predictive model for such resistance remains unestablished. This study aims to develop a machine learning model to predict the occurrence of CAAs prior to initiating IVIG therapy. Methods: Data from two nationwide epidemiological surveys conducted between 2012 and 2017 were analyzed, encompassing 17,189 patients with calculable coronary artery z-scores and Harada scores. Various supervised machine learning algorithms were applied to develop a model for predicting CAA. Afterward, unsupervised learning techniques were employed to explore the data’s inherent structure. Results: The Harada score’s receiver operating characteristic (ROC) analysis yielded an area under the curve (AUC) of 0.558. The highest AUC among the machine learning models was 0.661, achieved by the Light Gradient Boosting Machine. However, this model’s sensitivity was 0.615, and specificity was 0.647, indicating limited clinical applicability. Unsupervised learning revealed no distinct distribution patterns between patients with/without CAAs. Conclusions: Despite utilizing a large dataset to develop a machine learning-based prediction model for CAAs, the performance was unsatisfactory. Future studies should focus on enhancing predictive models by incorporating additional clinical data, such as acute-phase coronary artery diameter measurements, to improve accuracy and clinical utility. Full article
(This article belongs to the Special Issue Updates on Kawasaki Disease)
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