Global collaboration and innovation in malignant cerebral edema research: a bibliometric perspective

Abstract

Aim: Malignant cerebral edema (MCE) is a life-threatening complication of acute brain injuries, with mortality rates exceeding 80% in the absence of treatment. Despite advancements in osmotic therapies and decompressive craniectomy (DC), MCE continues to pose substantial clinical challenges. This study systematically maps the evolution of MCE research (2005-2024) to identify key trends, research gaps, and future priorities.

Methods: A bibliometric analysis of 1,460 peer-reviewed articles from the Web of Science Core Collection was conducted using CiteSpace, VOSviewer, and Bibliometrix. Key metrics included publication trends, geographic and institutional contributions, keyword co-occurrence, citation networks, and co-authorship patterns.

Results: Annual publications increased from 55 in 2005 to 128 in 2024, progressing through three distinct phases: Foundational growth (2005-2009), consolidation (2010-2014), and rapid expansion (2015-2024). The United States (28.9%) and China (18.7%) dominated research output, with Harvard University and the University of California System leading institutional collaboration clusters. High-impact journals highlighted clinical advancements, including Stroke (h-index = 27). Keyword analysis demonstrated a thematic progression from blood-brain barrier pathophysiology to clinical innovations, including DC and emerging predictive modeling techniques incorporating machine learning. Landmark trials, including DECIMAL and HAMLET, validated early surgical intervention, while emerging trends have emphasized precision medicine and artificial intelligence (AI)-driven risk stratification.

Conclusion: The MCE research has transitioned from foundational pathophysiology to interdisciplinary clinical practice and data integration. However, critical gaps remain, including underrepresentation in pediatric research, disparities in global neurocritical care, and challenges in translational application. Future priorities should focus on biomarker discovery, equitable global collaborations, and AI-enhanced frameworks to transform survival into functional recovery worldwide.

Keywords: bibliometric analysis; blood–brain barrier; cytotoxic edema; decompressive craniectomy; global collaboration; malignant cerebral edema; neurocritical care; precision medicine.

Figure 1

The flowchart of this study.

Figure 2

Annual publications and TC in MCE research (2005–2024). Blue bars indicate several articles published each year, while the orange line indicates the TC accrued by papers published in that year.

Figure 3

Geographic distribution and international collaboration in MCE research. (A) Annual article output (2005–2024) for the top 10 countries. (B) Co-authorship network of countries, with node size proportional to publication volume and edge thickness indicating collaboration strength. (C) Collaboration density map indicating bilateral partnerships. Node color intensity reflects the mean citation rate of each country, and link width corresponds to the number of joint publications. (D) Chord diagram of inter-country collaborations. (E) Horizontal bar chart of corresponding author countries, comparing SCP (teal) versus MCP (salmon).

Figure 4

Institutional productivity, collaboration networks, clustering, and thematic evolution in MCE research. (A) Stacked annual article output bar chart for the top 10 contributing institutions between 2005 and 2024. (B) Institution-level co-authorship network. Node size is proportional to total publications; edge thickness reflects collaboration frequency. Nodes are colored by modularity class, highlighting three major collaborative clusters centered around Harvard (red), the University of California system (blue), and the University of Maryland network (green). (C) Overlay visualization of the co-authorship network, with node color indicating the average publication year of each institution and node size proportional to publication volume. (D) Bubble-timeline of annual outputs for leading institutions. (E) Modularity-based clustering map of institutions. Nodes are sized by total output and colored by the assigned community; semi-transparent halos delineate each cluster. Cluster labels correspond to thematic specializations identified through institutional co-authorship patterns. (F) Thematic evolution of institutional research foci over time. Each horizontal track represents one of the 10 major research themes. Bubble size in a given year indicates the volume of publications within that theme, revealing shifts from early molecular studies to emerging clinical and translational topics.

Figure 5

Journal dissemination patterns, co-citation network structure, thematic clustering, and citation bursts in MCE research. (A) Annual article output (2005–2024) for the top 10 journals. (B) Journal co-citation network. (C) Betweenness-centrality overlay on the co-citation network. (D) Dual map of MCE research. (E) Spatial clustering map of co-cited journals. (F) Timeline view of journal citation bursts. Each horizontal track corresponds to a journal experiencing a burst.

Figure 6

Author productivity, co-authorship networks, clustering, and publication timelines in MCE research. (A) Scatterplot of individual authors. (B) Co-authorship network overlay highlighting author centrality. (C) Modularity-based clustering of the co-authorship network. (D) Timeline linkage of top authors to their primary research clusters.

Figure 7

Keyword co-occurrence patterns, thematic clustering, temporal dynamics, and citation bursts in MCE research. (A) Global keyword co-occurrence network with node size proportional to co-occurrence frequency. (B) Modularity-based clustering of the keyword network. (C) Overlay of the co-occurrence network by average occurrence year. (D) Temporal evolution map of keyword networks (2005–2024). (E) Bar chart of the top 25 keywords with the strongest citation bursts.

Figure 8

Integrated visualization of keyword prominence, temporal trends, co-occurrence clustering, and co-citation cluster timelines in MCE research. (A) Treemap of the most frequent keywords. (B) Wordcloud of keywords. (C) Trend-topics bubble-plot (2005–2024). (D) Keyword co-occurrence network clustering. (E) Co-citation cluster timeline view.

Figure 9

Reference co-citation network structure, clustering, temporal overlay, and strongest citation bursts in MCE research. (A) Global co-citation network of references. (B) Modularity-based clustering of the co-citation network. (C) Temporal overlay of the co-citation network. (D) Bar chart of the top 15 references with the strongest citation bursts.