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. 2022 Dec 9:13:1091999.
doi: 10.3389/fendo.2022.1091999. eCollection 2022.

Bibliometric and visualization analysis of literature relating to diabetic erectile dysfunction

Fanchao Meng  1 , Xiaoxing Liao  1 , Haimin Chen  2 , Sheng Deng  3 , Lu Wang  4 , Mengjie Zhao  1 , Haibin Li  1 , Dong Liu  1 , Guojing Gao  1 , Haisong Li  5 , Jisheng Wang  5
Affiliations

Bibliometric and visualization analysis of literature relating to diabetic erectile dysfunction

Fanchao Meng et al. Front Endocrinol (Lausanne). .

Abstract

Introduction: Diabetic erectile dysfunction (DMED) refers to erectile dysfunction secondary to diabetes. Erectile dysfunction is characterized by a persistent inability to achieve and maintain an erection sufficient to permit satisfactory sexual activity.

Methods: Based on the Web of Science core collection database, we firstly analyzed the quantity and quality of publications in the field of DMED, secondly profiled the publishing groups in terms of country, institution, author's publication and cooperation network, and finally sorted out and summarized the hot topics of research.

Results: From 2001 to 2022, a total of 1,403 articles relating to this topic were published in 359 journals. They represent the global research status, potential hotspots, and future research directions. The number of DMED-related publications and citations has steadily increased over the few past decades. Academic institutions from Europe and the United States have played a leading role in DMED research. The country, institution, journal, and author with the most publications were the United States (294), INHA University (39), the Journal of Sexual Medicine (156), and Ryu, Ji-Kan (29), respectively. The most common keywords were erectile dysfunction (796), men (256), diabetes (254), diabetes mellitus (239), prevalence (180), corpus cavernosum (171), dysfunction (155), mellitus (154), nitric-oxide synthase (153), and expression (140). The main keyword-based research topics and hotspots in the DMED field were oral sildenafil, smooth muscle relaxation, nitric oxide synthase, gene therapy, metabolic syndrome, cavernous nerve injury, stem cell, and penile prosthesis.

Discussion: The terms oral sildenafil, smooth muscle relaxation, nitric oxide synthase, gene therapy, metabolic syndrome, cavernous nerve injury, stem cell, and penile prosthesis will be at the forefront of DMED-related research.

Keywords: CiteSpace; VOSviewer; bibliometric analysis; diabetic erectile dysfunction; visualization.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Search flowchart.
Figure 2
Figure 2
Annual trends of global publications.
Figure 3
Figure 3
Analysis of the global research trends based on the origins of the publications.
Figure 4
Figure 4
Co-occurrence map of countries/regions. The size of the nodes represents the number of articles. The thickness of the curves represents the strength of collaboration. The colors represent different collaboration groups.
Figure 5
Figure 5
Co-occurrence map of institutions. The node size represents the number of articles; the curve thickness represents the strength of collaboration; the different collaboration groups are sorted by color.
Figure 6
Figure 6
CiteSpace visualization map of authors involved in publications related to assisted reproduction. Nodes represent authors (the larger the circle, the greater the number of publications). The lines between nodes represent the cooperation between two authors of the same article (the wider the line, the more frequent the cooperation). The node color represents the year.
Figure 7
Figure 7
Analysis of cited journals.
Figure 8
Figure 8
The 19 references with the strongest citation bursts.
Figure 9
Figure 9
Keyword analysis. (A) Map of the keyword co-occurrence analysis obtained using VOSviewer. The size of the nodes represents the number of occurrences; the thickness of the curve represents the strength of collaboration; the different colors represent the different clusters. (B) Keyword density visualization analysis. The redder the node color, the higher the frequency of the keyword. (C) Keyword clustering map analysis using CiteSpace. A total of 16 categories of keywords were obtained; the different color blocks represent different keyword clusters.
Figure 10
Figure 10
Keyword burst analysis using CiteSpace.
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