Abstract
BACKGROUND: Hyperuricemia (HUA) is a significant public health issue, ranking second only to diabetes in prevalence. While existing research demonstrates a robust correlation between these two conditions, the precise etiological mechanisms remain inadequately elucidated. This study utilized scientometric analysis to investigate the global association between HUA and diabetes. METHODS: Data on HUA and diabetes were retrieved from the Web of Science Core Collection database, encompassing the period from its inception until September 30, 2024. Collaboration networks were examined using VOSviewer, cluster analysis was executed with CiteSpace, and systematic mapping was conducted using Bibliometrix. RESULTS: By September 30, 2024, 1,464 studies indicated a consistent yearly increase in publications connecting HUA and diabetes despite some fluctuations. The lead authors were Richard J. Johnson, Miguel A. Lanaspa, and Masanari Kuwabara, with most contributors from China, the United States, and Japan. Key institutions include China Medical University, Shanghai Jiao Tong University, and Capital Medical University. The most published journal was Nutrition, Metabolism and Cardiovascular Diseases (CVDs), whereas the most cited journal was Diabetes Care. The reference network from 1987 to September 30, 2024, identified 19 clusters highlighting key research areas in HUA and diabetes, such as metabolic syndrome, uropathology, chronic kidney disease (CKD), and CVD. Exploring pathological mechanisms and pharmacological interventions linked to diabetes concomitant with HUA has emerged as a focal point of research and a burgeoning trend within the field. CONCLUSION: This study is the first scientometric analysis to synthesize research trends on HUA and diabetes, revealing molecular mechanisms and treatment strategies and providing theoretical insights for future clinical use.