Hotspots and development frontiers of postoperative complications of AD: Bibliometric analysis – a review. Issue 10 (10th March 2023)

• Record Type: Journal Article
• Authors: Feng, Danni; Huang, Sufang; Wang, Quan; Lang, Xiaorong; Liu, Yuchen; Zhang, Kexin
• Is Part Of: Medicine. Volume 102:Issue 10(2023)
• Page Start: e33160
• Publication Date: 2023-03-10
• Subjects: aortic dissection -- bibliometric analysis -- CiteSpace -- complication -- visualization -- VOSviewer; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000033160
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract : The research on the postoperative complications of aortic dissection (AD) has received great attention from scholars all over the world, and the number of research articles in this field has consistently increased year after year. However, no bibliometric reports have been published yet to analyze the scientific output and the current situation in this field. The Bibliometrix R-package, VOSviewer, and CiteSpace software were used to conduct a bibliometric analysis of the hotspots and development frontiers of AD. A total of 1242 articles were retrieved. The USA, China, and Japan had the highest number of publications. The five keywords with the highest frequency were "analysis, " "incidence, " "acute type, " "graft, " and "risk factor." The results also indicated that the research in related fields had shifted from surgical treatment and utilizing experience to the evidence-based exploration of risk factors and the construction of prediction models to help better manage postoperative complications of AD. This is the first bibliometric analysis of global publications on the postoperative complications of AD. The current research hotspots focus on three areas: common postoperative complications of AD, exploration of the related risk factors, and management of complications. Future research could focus on identifying risk factors through meta-analysis and using a multicenter database for AD as well as building relevant models to predict the development of complications to better facilitate the clinical management of AD patients.