基于VOSviewer和CiteSpace的中医药治疗非特异性下腰痛的可视化分析*

作者：卞正航1，许金海1,2，刘明慧1，方仪德1，薛瑞瑞1，莫 文1,2

单位：1.上海中医药大学附属龙华医院，上海 200032；2.石筱山伤科学术研究中心，上海 200032

引用：引用：卞正航，许金海，刘明慧，方仪德，薛瑞瑞，莫文.基于VOSviewer和CiteSpace的中医药治疗非特异性下腰痛的可视化分析[J].中医药导报,2026,32(3):185-192.

DOI：10.13862/j.cn43-1446/r.2026.03.029

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摘要：目的：探讨中医药治疗非特异性下腰痛（NLBP）临床研究的现状、热点及发展趋势，为今后的学术研究提供参考与借鉴。方法：检索中国知网（CNKI）、维普中文期刊服务平台（CSTJ）、万方数据知识服务平台（Wanfang Data）及Web of Science数据库（建库至2025年5月31日），筛选中医药干预NLBP的临床文献。采用NoteExpress去重整理，运用CiteSpace和VOSviewer对作者、机构及关键词进行可视化计量分析。结果：共纳入文献501篇（中文460篇，英文41篇），2000—2025年间年度发文量呈波动增长，分为起步期（2000—2013年）、迅速发展期（2014—2020年）和平稳发展期（2021—2024年）3个阶段。作者与合作机构分析显示，中英文文献的作者及机构间合作均较为松散，未形成紧密协同网络。关键词分析表明，中文研究聚焦于“慢性非特异性下腰痛”“针灸”“推拿疗法”“中药”等临床治疗与疗效评价；英文研究则更关注“management”“disability”等疾病管理与功能改善。聚类与时间演化分析进一步揭示，研究热点从单一针灸疗法逐步拓展至推拿、运动疗法、电针及针药结合等综合治疗模式，并趋向于结合现代评估指标（如疼痛程度、腰椎功能、生活质量）进行多维度效果评价，呈现多方法融合与精细化、个性化的发展趋势。结论：中医药治疗NLBP的研究逐渐深入，具有广阔的发展前景。未来研究应加强多学科合作，提高临床研究质量，注重基础实验与临床应用的结合，深入解析作用机制。同时，应充分利用现代医学技术和人工智能，实现精准化、智能化治疗，促进该领域的可持续创新发展。此外，应构建基于病程阶段的“评估-干预-管理”三级体系，以提高治疗效果和患者生活质量。

关键词：非特异性下腰痛；腰痛；中医药；VOSviewer；CiteSpace；文献计量；可视化分析

Abstract：

Objective: To explore the current situation, hotspots, and development trends of clinical research on traditional Chinese medicine (TCM) in the treatment of non-specific low back pain (NLBP), aiming to provide references for future academic research. Methods: Databases including China National Knowledge Infrastructure (CNKI), VIP Chinese Journal Service Platform (CSTJ), Wanfang Data Knowledge Service Platform (Wanfang Data) and Web of Science were searched from the establishment of each database to May 31, 2025, and clinical literatures on TCM intervention for NLBP were screened. NoteExpress was used for duplicate removal, and CiteSpace and VOSviewer were applied to conduct visual bibliometric analysis on authors, institutions and keywords. Results: A total of 501 literatures were included (460 in Chinese and 41 in English). The annual number of publications from 2000 to 2025 showed a fluctuating growth trend, which was divided into three stages: the initial stage (2000-2013), the rapid development stage (2014-2020) and the stable development stage (2021-2024). The analysis of authors and cooperative institutions indicated that the cooperation among authors and institutions in both Chinese and english literatures was relatively loose, and no closely collaborative network was formed. Keyword analysis showed that Chinese studies focused on clinical treatment and efficacy evaluation such as "chronic non-specific low back pain", "acupuncture", "tuina therapy" and "Chinese herbal medicine", while english studies paid more attention to disease management and functional improvement such as "management" and "disability". Cluster and temporal evolution analysis further revealed that research hotspots gradually expanded from a single acupuncture therapy to comprehensive treatment models such as tuina, exercise therapy, electroacupuncture and combination of acupuncture and herbal medicine, and tended to conduct multi-dimensional efficacy evaluation combined with modern assessment indicators (such as pain degree, lumbar function and quality of life), showing a development trend of integration of multiple methods, refinement and personalization. Conclusion: The research on TCM in the treatment of NLBP has been gradually deepened and has broad development prospects. Future studies should strengthen multidisciplinary cooperation, improve the quality of clinical research, focus on the combination of basic experiments and clinical application, and further analyze the mechanism of action. At the same time, modern medical technology and artificial intelligence should be fully utilized to achieve precise and intelligent treatment and promote the sustainable innovation and development of this field. In addition, a three-level "assessment-intervention-management" system based on disease course stages should be constructed to improve the therapeutic effect and patients' quality of life..

Key words：non-specific low back pain; low back pain; traditional Chinese medicine; VOSviewer; CiteSpace; bibliometrics; visual analysis

发布时间：2026-03-28

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