A bibliometric analysis of the research hotspots and frontiers related to cell death in spinal cord injury

Abstract

Background: Spinal cord injury (SCI) is a severe central nervous trauma that can cause serious consequences. Cell death is emerging as a common pathogenesis after SCI. In the last two decades, numerous studies have been published in the field of cell death after SCI. However, it is still rare to find relevant bibliometric analyses. This bibliometric study aims to visually represent global research trends in the field of cell death after SCI.

Methods: Bibliometric data were sourced from the Web of Science Core Collection (WoSCC) database. VOSviewer, CiteSpace, and R software ("bibliometrix" package) were used to analyze and visualize bibliometric data. Annual scientific production, countries/regions, institutions, authors, journals, highly cited papers, keywords, and literature co-citation were evaluated to determine research performance.

Results: An analysis of 5,078 publications extracted from the WoSCC database revealed a fluctuating yet persistent growth in the field of cell death after SCI over the past 23 years. China and the United States, contributing 69% of the total publications, were the main driving force in this field. The Wenzhou Medical University from China contributed to the most papers. In terms of authors, Salvatore Cuzzocrea from the University of Messina had the highest number of publications. The "Journal of Neurotrauma" was the top journal in terms of the number of publications, however, the "Journal of Neuroscience" was the top journal in terms of the number of citations. The theme of the highly cited articles mainly focused on the mechanism of cell death after SCI. The keyword and literature co-citation analysis mainly focused on the mode of cell death, mechanism research of cell death, and functional recovery after SCI.

Conclusion: This study analyzes the research hotspots, frontiers, and development trends in the field of cell death after SCI, which is important for future studies.

Keywords: apoptosis; bibliometric analysis; cell death; research hotspots; spinal cord injury.

Figure 1

The annual scientific publication of research in the field of cell death after SCI from 2000 to 2022 in the WoSCC database.

Figure 2

VOSviewer was employed to conduct a country/region co-authorship analysis. The overlay visualization map portrays each node as a country/region, wherein the connections between nodes symbolize the co-authorship associations. The magnitude of each node is directly proportional to the overall count of publications attributed to that particular country. Moreover, the hue of each node corresponds to the average year of appearance, as indicated by the color gradient in the lower right corner of the map.

Figure 3

Institution co-authorship analysis by VOSviewer. Each organization is represented as a node, and the node size is proportional to the sum of publications.

Figure 4

(A) The VOSviewer software was utilized to analyze author co-authorship. The resulting cluster density map visually represents authors who share a close relationship, as they are grouped within clusters of the same color. (B) The VOSviewer software was employed to perform an analysis of author co-citation. The resulting network visualization map depicts each author as a node, while the lines connecting these nodes represent the co-citation relationships between them.

Figure 5

Journal co-citation analysis by VOSviewer. Each node represents a journal and the node size is proportional to the number of co-citations by that journal.

Figure 6

Co-occurrence analysis of keywords: (A) The visualization map of keyword co-occurrence analysis includes an overlay, where the color of each node corresponds to the average annual yield, as indicated by the color gradient in the lower right corner. Nodes marked with purple or blue represent keywords that appeared earlier, while those coded in red represent current research focuses. (B) The network visualization map of keyword co-occurrence analysis demonstrates the clustering of closely related keywords, assigned the same color within each cluster.

Figure 7

Keyword cluster map.

Figure 8

Keywords with strongest citation bursts by CiteSpace. In the first column, “keywords” represented the theme terms. In the second column, “year” represented the year in which a theme term first appeared. In the third column, “strength” represented the citation bursts strength of these terms. In the fourth column, “begin” represented the starting year of a theme term burst. In the fifth column, “end” represented the end year of a theme term burst.

Figure 9

Literature co-citation analysis. Clusters are represented by color, nodes by size, and co-citations by link thickness.