Bibliometric Analysis of Research Trends and Global Collaborations in Anesthesia on Neuromuscular Blockers and Antagonists (2000–2024)

Figures

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  Figure 1. Flowchart.

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  Figure 2. The number of times cited and the number of publications over time. The citations in this graph represent the number of citations received in each individual year. The publication bars indicate the number of articles published per year within the same dataset.

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  Figure 3. The number of publications by year, with a linear regression analysis. The plot was generated using the Python sklearn and matplotlib libraries. The data cover the publication years from 2000 to 2024, with the blue dots representing the annual publication counts and the red line depicting the linear regression trend. The position of each dot indicates the yearly total for publications, while the slope of the regression line illustrates the overall upward trajectory in publication frequency.

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  Figure 4. Country Collaboration Network in NMBAs research. Visualization created using VOSviewer software. Nodes represent individual countries involved in research collaboration, with node size corresponding to frequency of country’s research output. Connecting lines illustrate collaborative relationships between countries, with thicker links indicating stronger cooperation. Colors indicate clusters of countries with stronger intra-group collaboration links, as identified by VOSviewer’s clustering algorithm.

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  Figure 5. The Journal Co-Citation Network in NMBAs research. The visualization was generated with VOSviewer software. Each node represents an academic journal, with the size indicating the frequency of published articles from the dataset. The links between nodes illustrate citation or co-citation relationships between journals; thicker lines suggest stronger connections. The journals are grouped into color-coded clusters based on citation patterns, indicating related research areas or publication themes within the field of anesthesiology and related specialties.

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  Figure 6. The Co-Authorship Network in NMBAs Research. The visual representation of co-authorship networks was generated by VOSviewer. Each node represents an individual author, while the links indicate co-authorship links. The colors group authors into clusters who collaborate more frequently. The thickness of the links reflects the strength of cooperation or shared publications, and the node size is proportional to each author’s prominence in the network.

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  Figure 7. Paper co-citations. Visualization of paper clusters produced by CiteSpace. Each colored region represents cluster of highly co-cited papers; node size reflects citation frequency; links indicate co-citation relationships.

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  Figure 8. The Top 20 References with the Strongest Citation Bursts. A display of the top 20 references with the strongest citation bursts from 2000 to 2024, as identified by CiteSpace. Each row lists the reference, its burst strength, and the time interval (beginning and end years). The colored bars illustrate the duration of the burst period (in red) against the broader timeline (in blue).

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  Figure 9. Keywords co-occurrence network. Network visualization of anesthesia-related keywords, with node size corresponding to frequency of keyword occurrence. Links represent co-occurrences of terms in the literature, and color-coded clusters highlight distinct thematic groupings. Map illustrates key research areas and connections among anesthetic agents and techniques.

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  Figure 10. The Sankey diagram of keywords. A Sankey diagram tracing the evolution of anesthesia-related topics over four time periods. Each colored block in a given interval represents a key theme in the diagram, and the connecting flows show how research focus shifts or overlaps across subsequent periods. The thickness of each flow reflects the relative frequency or strength of the connection, illustrating how certain anesthesia subjects emerge, persist, or decline over time.

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  Figure 11. The top 25 keywords with the strongest citation bursts. A list of the top 25 anesthesia-related keywords exhibiting the strongest citation bursts between 2000 and 2024, as determined by CiteSpace. Each row shows the keyword, its burst strength, and the start/end years of the citation surge. The red portion of each timeline indicates the burst period, while the blue portion reflects the full-time range under study.