Theme hotspots and knowledge structure of PCOS: Social network analysis and visualization study based on keywords

被引:0
|
作者
Wang, Yanjun [1 ]
Ding, Jinli [1 ]
Min, Yuguo [2 ]
Zhang, Yuyin [1 ]
Ming, Junren [2 ]
Yin, Tailang [1 ,3 ]
机构
[1] Wuhan Univ, Reprod Med Ctr, Renmin Hosp, Wuhan 430060, Hubei, Peoples R China
[2] Wuhan Inst Technol, Sch Management, Wuhan 430079, Hubei, Peoples R China
[3] Wuhan Univ, Shenzhen Res Inst, Shenzhen, Guangdong, Peoples R China
关键词
infertility; literature visualization; metabolic syndrome; PCOS; social network analysis; POLYCYSTIC-OVARY-SYNDROME; INSULIN-RESISTANCE; WOMEN; ASSOCIATION; HORMONE; SHBG; RISK;
D O I
10.1002/ijgo.70108
中图分类号
R71 [妇产科学];
学科分类号
100211 ;
摘要
Background Polycystic ovarian syndrome (PCOS) is the most common endocrine disease in women. Many scholars have explored the basic and clinical research of PCOS. However, there is still a lack of research on knowledge structure, bibliometric analysis, and visualization results in the PCOS field. Objective The main purpose of our study was to analyze the current research status of PCOS and explore hotspots and weak points through social network analysis (SNA) and visualization study, providing ideas and opinions for follow-up researchers. Methods Reports on PCOS in the literature published from January 2018 to October 2022 were collected from the Web of Science database. Based on the statistics of keywords, a co-word network was generated and used to calculate network indicators. The current research hotspots and research trends of PCOS were analyzed with descriptive statistics, co-occurrence analysis, and SNA. Results A total of 9282 unique keywords (total frequency 29 847) were obtained from 5828 papers, and 121 high-frequency keywords were selected with frequencies greater than or equal to 20. Keywords including insulin resistance, hyperandrogenemia, metabolic syndrome, and overweight rank within the top five in the centrality of these keywords. By network calculation, the PCOS SNA network was divided into eight clusters (C1-C8): C1, reproduction; C2, pathogenesis; C3, related diseases; C4, clinical manifestation; C5, hormone regulation; C6, clinical management; C7, new regulatory factors; and C8, gene polymorphism. Clusters 3, 4, and 6 have higher density, and clusters 1, 3, and 4 have higher degree. Conclusions This study reveals the research hotspots and structure of PCOS in recent years through SNA and visualization techniques. We conclude that PCOS is closely related to female reproduction. Although the pathogenesis of PCOS is still unclear, insulin resistance may be the key research topic. Hormone regulation is critical for PCOS, and PCOS patients require careful clinical management. We need more research on the genetics of the disease and new regulatory mechanisms. Our findings will provide reliable and valid support to researchers, funders, policymakers, and clinicians.
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页数:13
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