Knowledge graph visualization and bibliometric analysis of research on coronary artery lesions in Kawasaki disease

BACKGROUND: Coronary artery lesions (CAL) complicating Kawasaki disease (KD) are a central concern affecting the long-term cardiovascular health of affected children. This study aimed to systematically depict the macro landscape, knowledge structure, and evolutionary dynamics of this field through bibliometric and knowledge graph methods, providing strategic guidance for future research. METHODS: Literature related to KD-CAL was retrieved from the Web of Science Core Collection. Quantitative and visual analyses of publication trends, countries/regions, institutions, authors, journals, references, and keywords were conducted using CiteSpace 6.3.R1, VOSviewer 1.6.20, and the Bibliometrix R package. RESULTS: A total of 2655 publications were included. The annual publication volume showed an increasing trend, with acceleration after 2015. The United States emerged as the country with the highest productivity and influence (citation frequency, centrality), while China ranked first in publication output (909 articles) but had a lower rate of international collaboration (MCP_Ratio = 0.08). The core journal cluster comprised Circulation, Journal of Pediatrics, and Pediatric Cardiology, among others. A close international collaboration network was formed around key figures like Jane Carleton Burns and Adriana H. Tremoulet. Keyword and document co-citation analyses revealed 5 major research clusters: acute-phase management, immunopathological mechanisms, coronary complications, treatment of intravenous immunoglobulin resistance, and long-term follow-up. The research frontier has evolved from "epidemiology" and "diagnosis" to "biomarkers" and "IVIG resistance," and is now predominantly focused on "biologics" (e.g., infliximab, anakinra) and "artificial intelligence/machine learning." CONCLUSION: The new phase of KD-CAL research may focus on precision medicine. Future efforts may focus on deepening immunological mechanism studies to develop targeted therapies, utilizing artificial intelligence to optimize risk stratification and imaging assessment, and establishing globally collaborative long-term cohorts to clarify cardiovascular outcomes in adulthood. Strengthening basic and clinical translation is essential to advance KD-CAL diagnosis and treatment into a new era of precision and efficiency.