Knowledge domain and emerging trends in diabetic cardiomyopathy: A scientometric review based on CiteSpace analysis

Abstract

ObjectiveTo review the literature related to diabetic cardiomyopathy (DCM), and investigate research hotspots and development trends of this field in the relevant studies based on CiteSpace software of text mining and visualization in scientific literature.MethodsThe relevant literature from the last 20 years was retrieved from the Web of Science (WoS) Core Collection database. After manual selection, each document record includes title, authors, year, organization, abstract, keywords, citation, descriptors, and identifiers. We imported the downloaded data into CiteSpace V (version 5.8.R2) to draw the knowledge map and conduct cooperative network analysis, cluster analysis, burst keyword analysis, and co-citation analysis.ResultsAfter manual screening, there were 3,547 relevant pieces of literature published in the last 18 years (from 2004 to 2021), including 2,935 articles and reviews, which contained 15,533 references, and the number was increasing year by year. The publications of DCM were dedicated by 778 authors of 512 institutions in 116 countries. The People's Republic of China dominated this field (1,117), followed by the USA (768) and Canada (176). In general, most articles were published with a focus on “oxidative stress,” “heart failure,” “diabetic cardiomyopathy,” “dysfunction,” “cardiomyopathy,” “expression,” “heart,” “mechanism,” and “insulin resistance.” Then, 10 main clusters were generated with a modularity Q of 0.6442 and a weighted mean silhouette of 0.8325 by the log-likelihood ratio (LLR) algorithm, including #0 heart failure, #1 perfused heart, #2 metabolic disease, #3 protective effect, #4 diabetic patient, #5 cardiac fibrosis, #6 vascular complication, #7 mitochondrial dynamics, #8 sarcoplasmic reticulum, and #9 zinc supplementation. The top five references with the strongest citation bursts include “Boudina and Abel”, “Jia et al.”, “Fang et al.”, “Poornima et al.”, and “Aneja et al.”.ConclusionThe global field of DCM has expanded in the last 20 years. The People's Republic of China contributes the most. However, there is little cooperation among authors and institutions. Overall, this bibliometric study identified the hotspots in DCM research, including “stress state,” “energy metabolism,” “autophagy,” “apoptosis,” “inflammation,” “fibrosis,” “PPAR,” etc. Thus, further research focuses on these topics that may be more helpful to identify, prevent DCM and improve prophylaxis strategies to bring benefit to patients in the near future.

A Bibliometric Visualization Analysis on Vaccine Development of Coronavirus Disease 2019 (COVID-19)

“…The centrality indicator for the nodes of the co-citing network is betweenness centrality. The indicator of centrality is used to assess the literature’s importance and the level of each piece of literature as part of a co-citation [ 17 ]. In the CiteSpace, the normalized value of centrality is between 0 and 1, and the nodes with high centrality scores are important documents in a co-cited network [ 17 ].…”

“…The indicator of centrality is used to assess the literature’s importance and the level of each piece of literature as part of a co-citation [ 17 ]. In the CiteSpace, the normalized value of centrality is between 0 and 1, and the nodes with high centrality scores are important documents in a co-cited network [ 17 ]. For the keywords of citation bursts, the burst detection algorithm can be suitable to measure sharp increases in interest within a short timespan [ 18 ].…”

“…A silhouette value above 0.7 (S > 0.7) is considered an efficient and convincing cluster [ 19 ]. If the value of modularity is more than 0.3 (Q > 0.3), this means that the network is significant [ 17 ]. The parameter settings, including time slicing (2019 to 2022, one year per slice), term source (all selected), node type (one at a time), and a selection criterion (g-index = 25 in each slice) were selected while creating a visualization analysis with CiteSpace in the current study [ 20 ].…”

“…The fourth largest cluster (#3), labeled ‘COVID-19 vaccine’ by keywords, indicated that the safety and effectiveness of vaccination is another important focus hotspot in the COVID-19 vaccine research field. Among the top ten most cited publications, three papers in this cluster, which reported the results of safety and effectiveness of three vaccines, the ChAdOx1 nCoV-19 vaccine (AZD1222), the BNT162b2 mRNA vaccine, and the mRNA-1273 vaccine, yielded more than 4760 citations [ 17 , 18 , 20 ]. In a recent systematic review and meta-analysis, outcomes suggest that COVID-19 vaccines are effective in reducing the incidence of SARS-CoV-2 infection and have negligible adverse effects; this confirmed the effectiveness and safety of the COVID-19 vaccine after vaccination [ 51 , 52 ].…”

Global research trends between gut microbiota and lung cancer from 2011 to 2022: A bibliometric and visualization analysis

“…CiteSpace (Version 5.6.R3) was regarded as an excellent visualization tool invented by Professor Chaomei Chen, which was widely used for countries, journals, dual-map analysis, institutions, cited references, and timeline view and for detecting the keywords with strong citation bursts (24,25). The parameters of CiteSpace were set as follows: time slicing was from 2011 to 2022, years per slice (1); selected one node type at a time; and selection criteria were the top 50 objects.…”