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冠状动脉慢性完全闭塞病变研究热点及趋势的可视化分析

Visualization analysis of research hotspots and trends of chronic total occlusion
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摘要 目的对冠状动脉(冠脉)慢性完全闭塞病变的相关文献进行可视化呈现,以分析其研究热点和发展趋势。方法通过检索2000年至2022年发表在中国知网数据库上的文献,初步筛选后导入Citespace软件去重,生成关键词共线、突现、聚类、峰峦、时间线和时区图谱,从而进行可视化分析。结果共检索到文献539篇,经过筛选后剔除19篇,经过去重后最终纳入分析的文献510篇。年度发文量在整体上呈现出了持续稳步增长的趋势,具有较大的发展前景和上升空间。关键词共线和突现分析显示,目前经皮冠状动脉介入治疗(PCI)、预后等研究方向是冠脉慢性完全闭塞病变的研究热点,但发文量不多。结论冠脉慢性完全闭塞病变PCI治疗预后研究是未来的发展方向,应开展更多的预后预测模型研究,并促进模型的临床转化和应用。 Objective The relevant literature on chronic total occlusion was visualized to analyze its research hotspots and development trends.Methods By searching the literature published on the CNKI database from 2000 to 2022,after preliminary screening,Citespace software was introduced to remove duplicates,and keywords co-line,burst,clustering,landscape,timeline and time zone maps were generated for visual analysis.Results A total of 539 articles were retrieved,19 articles were excluded after screening,and 510 articles were finally included in the analysis after deduplication.The annual number of publications shows a trend of sustained and steady growth as a whole,with great development prospects and rising space.Co-line and burst analysis of keywords showed that the current research directions of percutaneous coronary intervention and prognosis were the research hotspots of chronic total occlusion,but the number of publications was not large.Conclusion The prognostic study of percutaneous coronary intervention for chronic total occlusion is the future development direction.More prognostic prediction model studies should be carried out,and the clinical transformation and application of the model should be promoted.
作者 覃胜德 徐广马 罗美凤 邱雪 Qin Shengde;Xu Guangma;Luo Meifeng;Qiu Xue(Graduate School of Youjiang Medical University for Nationalities,Baise 533000,China;不详)
出处 《中国循证心血管医学杂志》 2024年第1期13-17,共5页 Chinese Journal of Evidence-Based Cardiovascular Medicine
基金 广西医疗卫生适宜技术开发与推广应用项目(S2018022) 广西科学研究与技术开发计划项目(桂科攻14124003-9) 广西科技计划项目(桂科AD17129026)。
关键词 冠脉慢性完全闭塞病变 可视化分析 Chronic total occlusion Visualization analysis
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