Bibliometric Analysis of Non-Vitamin K Antagonist Oral Anticoagulants (NOACS) in the Prevention of Venous Thrombosis and Pulmonary Embolism

Figures

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  Figure 1. Flow chart of data collection and extraction of articles.

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  Figure 2. General information of non-vitamin K antagonist oral anticoagulants (NOACS) in the prevention of venous thrombosis and pulmonary embolism. (A). The rank of research by the number of publications. (B). The rank of affiliated institution based on publication count. (C). The rank of author by publications. (D). The rank of countries/regions on publications.

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  Figure 3. Cumulative publication counts of NOACs. (A). The line graph depicted illustrates the annual publication count. A linear regression analysis yielded the equation y = 15.62x-31314.32, R² = 0.9333. (B). The bar graph presents the cumulative number of papers published each year. A second-order polynomial regression equation was employed to ascertain that the yearly growth rate of papers adheres to y=7.46x²-29890.69x+29940466.85, R² = 0.9991.

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  Figure 4. Collaborative networks of authors and institutional cooperation. (A). The Author Collaboration Network comprises 11 distinct clusters, which were generated through keyword-based clustering analysis. Cluster #1 REGISTRY represents the largest cluster in terms of size, followed by Cluster #2 UNDERGOING TOTAL Hip REPLACEMENT as the second largest, and so forth. Among these clusters, the top five are identified as follows: Cluster #1 REGISTRY; Cluster #2 UNDERGOING TOTAL HIP REPLACEMENT; Cluster #3 EXTENDED THROMBOPROPHYLAXIS; Cluster #5 SHORTENED HOSPITAL LENGTH; and Cluster #6 FIRST UNPROVOKED VENOUS THROMBOEMBOLISM. (B). The network diagram illustrates the clustering of institutional cooperation based on keywords. Cluster #0 emerges as the largest cluster, followed by Cluster #1 as the second largest, and so forth. Amongst these clusters, the top five are identified as follows: Cluster #0 represents “UNDERGOING TOTAL HIP” Cluster #1 signifies “DABIGATRAN ETEXILATE” Cluster #2 denotes “WEEKLY RISK” Cluster #3 refers to “EXTENDED-DURATION THROMBOPROPHYLAXIS”, and finally, Cluster #4 is labeled as “CANCER-ASSOCIATED THROMBOEMBOLISM”.

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  Figure 5. Graphs of national distributions and cooperation networks. (A). Graphs of national cooperation networks were clustered by key words. The network consists of 7 clusters. Cluster #0 surgery is the largest Cluster, Cluster #1 compression is the second largest cluster, and so on. China, the country in Cluster #0 CASE REPORT, has the largest bursts Counts. USA has the most Citation Counts in Cluster #2 stroke. (B). A geographical visualization map illustrates the patterns of national cooperation, with interconnecting lines symbolizing their cooperative relationships.

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  Figure 6. The literature co-citation network. (A) The literature co-citation network diagram was constructed and clustered based on key words. The network comprised 13 clusters, with Cluster #0 secONDARY PREVENTION being the largest cluster consisting of 66 members. Following that, Cluster #1 RECURRENT VENOUS THROMBOEMBOLISM had 64 members, while Cluster #2 CANCER-ASSOCIATED VENOUS THROMBOEMBOLISM had 64 members. (B) is a density view of (A), using color intensity to represent the concentration and co-citation frequency of references. Highlighted areas indicate references that are frequently co-cited in literature, usually representing core research contributions in this field. Warmer color areas indicate strong associations between references, showing that these references are frequently cited together, thus reflecting the density and focus of related research. (C) presents a timeline evolution map of co-cited references, depicting the changes in research hotspots in the NOACs field from 2004 to 2024. Each circle represents a group of co-cited references, with the size reflecting the number of citations, while the color gradually changes from cool (earlier) to warm (recent), illustrating…

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  Figure 7. Graphs of keywords co-occurrence. (A). Keyword Clustering shows keyword clusters in NOACs research. Each bubble represents a keyword, with size indicating academic influence and color representing different time periods. These clusters highlight major themes such as “perioperative management”, “stroke prevention”, and “cancer-associated venous thromboembolism”. (B). Keyword Timeline Evolution presents a timeline of keywords from 2004 to 2024, showing the rise of research topics. Each diamond represents a keyword, with size indicating publication volume. Topics like “dabigatran etexilate” and “pulmonary embolism” have gained prominence in recent years. (C). Keyword Density View is a density view of (A), using color intensity to show the concentration of frequently co-occurring keywords. Warmer areas indicate higher concentrations, reflecting core research areas. (D). Keyword Burst Detection shows keyword burst analysis, indicating the strength and duration of research focus from 2004 to 2024. Keywords like “dabigatran etexilate” and “factor Xa inhibitor” have shown significant bursts, indicating intense academic interest.