基于CiteSpace软件对中医药治疗酒精性肝损伤的可视化分析

Visual Analysis of Traditional Chinese Medicine in the Treatment of Alcoholic Liver Injury Based on CiteSpace Software

摘要: 目的：可视化研究中医药治疗酒精性肝损伤相关文献，分析该领域的研究现状、研究热点及趋势。方法：检索中国知网(CNKI)数据库1994年1月至2026年7月收录的相关文献，应用CiteSpace 6.2.R3软件从作者合作网络、机构合作网络、关键词共现、关键词聚类、关键词时间线、关键词突现等方面进行可视化图谱分析。结果：共纳入文献536篇。年度发文量呈波动增长趋势，并于2012年达到峰值。核心作者以冯琴、赵文霞、李军祥等为代表，但作者合作网络整体密度偏低，大规模合作模式尚未形成。研究机构中，北京中医药大学、上海中医药大学及其附属医疗单位贡献突出，然而机构间中介中心性普遍较低，跨单位合作研究不足。关键词分析显示，研究热点集中于酒精性肝病、中医药疗法、中药、酒精性肝损伤等。关键词聚类分析共得到18个聚类，聚类结构显著且合理(Q = 0.8449, S = 0.9481)；关键词突现结果表明，近年来该领域正经历由传统临床疗效观察向深度分子机制研究的方法学转变，作用机制、网络药理学、数据挖掘及中药复方成为新兴研究热点。结论：中医药防治酒精性肝损伤的研究已进入稳定发展阶段，但核心作者与机构间的协同合作有待加强。未来研究应进一步深入研究中医药防治酒精性肝损伤的分子作用机制，并借助网络药理学与数据挖掘等新兴研究技术，深入阐释中药复方的多靶点调控机制，为后续研究提供参考依据。

Abstract: Objective: To visually study the literature related to alcoholic liver injury and traditional Chinese medicine treatment, and to analyze the research status, research hotspots and trends in this field. Methods: Relevant literatures included in CNKI database from January 1994 to July 2026 were searched, and CiteSpace 6.2.R3 software was used to conduct visual map analysis from the aspects of author cooperation network, institutional cooperation network, keyword co-occurrence, keyword clustering, keyword timeline, keyword burst and so on. Results: A total of 536 articles were included. The annual number of publications showed a fluctuating growth trend and peaked in 2012. The core authors are represented by Feng Qin, Zhao Wenxia, Li Junxiang, etc., but the overall density of the author cooperation network is low, and the large-scale cooperation model has not yet been formed. Among the research institutions, Beijing University of Chinese Medicine, Shanghai University of Chinese Medicine and their affiliated medical institutions have made outstanding contributions. However, the between-agency between institutions is generally low, and cross-unit cooperation research is insufficient. Keyword analysis showed that the research hotspots focused on alcoholic liver disease, traditional Chinese medicine therapy, traditional Chinese medicine, alcoholic liver injury, etc. A total of 18 clusters were obtained by keyword cluster analysis, and the cluster structure was significant and reasonable (Q = 0.8449, S = 0.9481). The results of keyword burst show that in recent years, this field is undergoing a methodological transformation from traditional clinical efficacy observation to in-depth molecular mechanism research. Mechanism of action, network pharmacology, data mining and traditional Chinese medicine compound have become emerging research hotspots. Conclusion: The research on the prevention and treatment of alcoholic liver injury by traditional Chinese medicine has entered a stage of stable development, but the collaboration between core authors and institutions needs to be strengthened. Future research should further study the molecular mechanism of traditional Chinese medicine in preventing and treating alcoholic liver injury, and use emerging research technologies such as network pharmacology and data mining to deeply explain the multi-target regulation mechanism of traditional Chinese medicine compound, so as to provide reference for follow-up research.