基于可视化软件和文献计量学方法，了解慢性心力衰竭（简称慢性心衰）动物模型研究情况，探索 慢性心衰动物模型的研究热点，指导动物实验和科研设计。方法检索Web of Science 核心合集从2001 年 1 月1 日至2022 年10 月10 日收录的慢性心衰动物模型相关文献，通过阅读全文得到最终纳入文献后，以 VOSviewer 与CiteSpace 程序软件分析机构、期刊和共被引期刊、作者和共被引作者、关键词等内容。结果共 纳入961 篇文献，年发文量稳中有升；美国和中国等是主要研究国家；约翰·霍普金斯大学和哈佛大学等是主 要研究机构；出版和被引用次数较多的期刊为AM J PHYSIOL-HEART C 和CIRCULATION 等；Schultz Harold D 和Sabbah Hani N是较有影响力的作者；myocardial infarction（心肌梗死）、cardiac hypertrophy（心脏肥大）和rat （大鼠）等是频数较高的关键词，生成10 个聚类与18 个突现词。结论该领域研究众多、质量较高但分散。常 用动物模型为鼠类和犬类；造模方法主要为手术和药物；病理机制以心肌肥厚、氧化应激和心肌纤维化为主。

To understand the research situation of animal model of chronic heart failure （CHF） based on visualization software and bibliometrics methods，and to explore the research hotspots of animal models of CHF and guide the design of animal experiments and scientific research. Methods Literature related to animal model of CHF included in Web of Science core collection from January 1，2001 to October 10，2022 were retrieved. After reading the full text and obtaining the final included literature， VOSviewer and CiteSpace software were used to analyze the contents of institutions， journals and co-cited journals， authors and co-cited authors， keywords. Results A total of 961 papers were included， and the number of published papers increased steadily. The United States and China are the main research countries. Johns Hopkins University and Harvard University are major research institutions. The most frequently published and cited journals are AM J PHYSIOL-HEART C and CIRCULATION，etc. . Schultz Harold D and Sabbah Hani N are more influential in author selection. “Myocardial infarction”，“cardiac hypertrophy”， and “rat” are the most frequent keywords， 10 clusters and 18 emergent words were formed. Conclusion The research in this field is numerous，high quality but scattered. Commonly used animal models are rodents and dogs. The main modeling methods are surgery and drugs. The main pathological mechanisms are mainly myocardial hypertrophy，oxidative stress，and myocardial fibrosis.

R-332；R285.5

国家自然科学基金项目（82274412）；湖南省自然科学基金项目（2023JJ30453）。