中医药治疗围绝经期抑郁症的CiteSpace可视化分析

CiteSpace-Based Visualization Analysis of Traditional Chinese Medicine for Perimenopausal Depression

摘要: 目的：基于文献计量学方法，探讨2002年至2025年中医药治疗围绝经期抑郁症(PMD)的研究现状、学术力量及前沿热点。方法：检索中国知网(CNKI)收录的中医药治疗PMD相关学术期刊文献。应用CiteSpace 6.4.R1软件，对纳入的329篇文献进行年度发文量、作者、机构、关键词共现、聚类及突现分析。结果：年度发文量自2007年稳步上升，2016年后维持高位波动。任路为产出最高的学者；辽宁、天津及黑龙江中医药大学是核心机构。研究热点集中于中西医结合、电针及5-羟色胺等。聚类分析显示，机制研究已深入至生殖内分泌及海马相关分子指标，侧重于中医药对环磷酸腺苷反应元件结合蛋白(CREB)等信号通路的微观调节。结论：中医药治疗PMD已形成以“补肾疏肝”为临床核心、以“神经内分泌调节”为机制主线的成熟格局。提升睡眠质量是近年的关注焦点，而利用网络药理学探讨多靶点协同机制是当前及未来的研究前沿。

Abstract: Objective: Based on bibliometric methods, to explore the research status, academic forces, and frontier hotspots of traditional Chinese medicine (TCM) in the treatment of perimenopausal depression (PMD) from 2002 to 2025. Methods: Academic journal literature related to TCM treatment for PMD indexed in China National Knowledge Infrastructure (CNKI) was searched. CiteSpace 6.4.R1 software was applied to conduct analysis on annual publication volume, authors, institutions, and keyword co-occurrence, clustering, and bursts for the 329 included documents. Results: Annual publication volume has increased steadily since 2007 and maintained high-level fluctuations after 2016. Ren Lu is the most prolific scholar; Liaoning, Tianjin, and Heilongjiang Universities of Chinese Medicine serve as the core institutions. Research hotspots center on integrated traditional Chinese and Western medicine, electroacupuncture, and 5-hydroxytryptamine. Cluster analysis reveals that mechanistic research has extended to reproductive endocrinology and hippocampal molecular indicators, focusing on the micro-regulation of signaling pathways such as the cyclic adenosine monophosphate response element-binding protein (CREB) by traditional Chinese medicine. Conclusion: TCM treatment of PMD has formed a mature pattern with “tonifying the kidney and soothing the liver” as the clinical core and “neuroendocrine regulation” as the main mechanistic thread. Improving sleep quality is a focus in recent years, while using network pharmacology to explore multi-target synergistic mechanisms represents the current and future research frontier.