Objectives: Robotic pancreaticoduodenectomy (RPD) has garnered significant research attention in the last decade. However, no bibliometric studies have been conducted on this field yet. Therefore, the aim of this study is to provide an up-to-date analysis of the current state of research, as well as future trends and hotspots in RPD, through a bibliometric analysis.
Materials and methods: We conducted a thorough search of all literature related to RPD in the Web of Science Core Collection (WoSCC). We then analyzed this literature for a variety of factors, including authorship, country of origin, institutional affiliations, and keywords. To visualize our findings, we utilized Citespace 6.1.R3, which enabled us to create network visualization maps, perform cluster analysis, and extract burst words.
Results: A total of 264 articles were retrieved. Zureikat is the author with the largest contribution in this field, and Surgical Endoscopy and Other International Techniques is the journal with the largest number of papers in this field. The United States is the core research country in this field. The University of Pittsburgh is the most productive institution. According to the data, outcome, pancreas fistula, definition, risk factor, stay, survival, learning curve and experience are recognized as research hotspots in this field.
Conclusions: This study is the first bibliometric study in the field of RPD. Our data will help us better understand the development trend of the field, and determine research hotspots and research directions. The research results provide practical information for other scholars to understand key directions and cutting-edge information.
Keywords: Bibliometric analysis; Minimally Invasive Pancreatoduodenectomy; Robot.
© 2023. The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.