Guo Zhihao, Zhang Zi, Li Lu, Zhang Ming, Huang Shanqing, Li Zezhi, Shang Dewei
Department of Pharmacy, The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, Guangzhou, China.
School of Pharmacy, Guangzhou Medical University, 1 Xinzao Road, Guangzhou, China.
Curr Neuropharmacol. 2025;23(4):439-457. doi: 10.2174/1570159X23666241016090634.
With the frequent use of antipsychotics, the metabolic disorder (MetD) caused by drugs has received increasing attention. However, the mechanism of drug-induced MetD is still unclear and is being explored. Keeping abreast of the progress and trending knowledge in this area is conducive to further work.
The aim of this study is to analyze the latest status and trends of research on antipsychoticinduced metabolic disorder (AIMetD) by bibliometric and visual analysis.
3478 publications of AIMetD from 2006 to 2021 were retrieved from the Web of Science Core Collection database. R-biblioshiny was used for descriptive analysis, CiteSpace for cooperative network, co-citation analysis and burst detection, and VOSviewer for co-occurrence keywords was used.
Since 2006, the publications have been growing fluctuantly. These studies have extensive cooperation among countries/regions. The most influential country/region, institution and author are the USA, King's College London and Christoph U Correll. Analysis of references shows the largest cluster of "antipsychotic-induced metabolic dysfunction", which is an important basis for MetD. The recent contents of the burst citation are related to "glucose homeostasis" and "cardiovascular metabolism". Several bursting keywords were discerned at the forefront, including "LC-MS/MS", "major depressive disorder", "expression", and "homeostasis".
The AIMetD study is in a state of sustained development. Close cooperation between countries/ regions has promoted progress. For grasping the foundation, development, and latest trends of AIMetD, it is recommended to focus on active institutions and authors. Based on AIMetD, subdivision areas such as "LC-MS/MS", "expression", and "homeostasis" are forefronts that deserve constant attention.
随着抗精神病药物的频繁使用,药物引起的代谢紊乱(MetD)受到越来越多的关注。然而,药物诱导的MetD机制仍不清楚,正在探索中。了解该领域的进展和最新知识有助于进一步开展工作。
本研究旨在通过文献计量学和可视化分析,分析抗精神病药物诱导的代谢紊乱(AIMetD)的研究现状和趋势。
从Web of Science核心合集数据库中检索2006年至2021年关于AIMetD的3478篇出版物。使用R-biblioshiny进行描述性分析,使用CiteSpace进行合作网络、共被引分析和突现检测,使用VOSviewer进行共现关键词分析。
自2006年以来,出版物数量呈波动增长。这些研究在国家/地区之间有广泛的合作。最具影响力的国家/地区、机构和作者分别是美国、伦敦国王学院和克里斯托夫·U·科雷尔。参考文献分析显示,最大的聚类是“抗精神病药物诱导的代谢功能障碍”,这是MetD的重要基础。近期突现引用的内容与“葡萄糖稳态”和“心血管代谢”有关。在前沿发现了几个突现关键词,包括“LC-MS/MS”、“重度抑郁症”、“表达”和“稳态”。
AIMetD研究处于持续发展状态。国家/地区之间的密切合作促进了进展。为掌握AIMetD的基础、发展和最新趋势,建议关注活跃的机构和作者。基于AIMetD,“LC-MS/MS”、“表达”和“稳态”等细分领域是值得持续关注的前沿领域。