近30年温病学说的研究现状可视化分析

Research Status and Trend Visualization Analysis of Febrile Disease Theory in the Past 30 Years

摘要: 目的：利用文献计量学方法分析温病学说的研究现状及热点。方法：检索1994年1月至2024年3月中国知网核心期刊数据库内收录的关键词为“温病”的研究文献。采用Excel2021绘制发文量趋势图，采用CiteSpace6.3.R1软件绘制关键词聚类、共现知识图谱，核心作者、机构贡献网络以及时间线图。结果：共纳入文献8874篇，该研究领域发文量呈波动上升。趋势1150位中文核心作者形成多个研究团队，各团队之间合作缺乏，发文机构主要为各中医药院校及其附属机构。热点关键词为“温病”“温病条辨”“用药规律”“瘟疫”等，共形成8个主要聚类，温病学、温病条辨、吴鞠通、辨证论治、叶天士、疫病等是该领域的主要研究方向。结论：目前该领域多从名医经验、临床应用、数据挖掘、教学改革、实验研究、中医教育等方面开展对温病学说的研究，同时疫病、数据挖掘、临床应用、实验研究的研究方向趋热。

Abstract: Objective: This study aims to analyze the current research status and emerging hotspots in the doctrine of Warm Diseases using a bibliometric approach. Methods: Articles with the keyword “Warm Disease” published between January 1994 and March 2024 were retrieved from the core journal database of CNKI. Excel 2021 was used to visualize the annual publication trends, while CiteSpace 6.3.R1 was employed to generate keyword co-occurrence and clustering maps, collaboration networks of core authors and institutions, and a timeline view of research themes. Results: A total of 8874 publications were included. The number of publications exhibited a fluctuating upward trend over the study period. Among the 4150 core authors identified, several research teams were formed, though inter-team collaboration remained limited. Major contributing institutions were primarily universities of traditional Chinese medicine and their affiliated hospitals. High-frequency keywords included “Warm Disease”, “Systematic Differentiation of Warm Diseases”, “medication rules”, and “plague”. The keyword clustering analysis identified 8 major groups, indicating that current research focuses on Warm Disease theory, Systematic Differentiation of Warm Diseases, Wu Jutong, syndrome differentiation and treatment, Ye Tianshi, and infectious diseases. Conclusion: Current research on the doctrine of Warm Diseases primarily revolves around clinical application, data mining, renowned physicians’ experiences, pedagogical reform, experimental investigation, and traditional Chinese medicine education. Topics such as infectious diseases, data mining, clinical applications, and experimental research are receiving growing attention.