{"title":"多囊卵巢综合征的主题热点和知识结构:基于关键词的社会网络分析和可视化研究。","authors":"Yanjun Wang, Jinli Ding, Yuguo Min, Yuyin Zhang, Junren Ming, Tailang Yin","doi":"10.1002/ijgo.70108","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":14164,"journal":{"name":"International Journal of Gynecology & Obstetrics","volume":" ","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Theme hotspots and knowledge structure of PCOS: Social network analysis and visualization study based on keywords.\",\"authors\":\"Yanjun Wang, Jinli Ding, Yuguo Min, Yuyin Zhang, Junren Ming, Tailang Yin\",\"doi\":\"10.1002/ijgo.70108\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>\",\"PeriodicalId\":14164,\"journal\":{\"name\":\"International Journal of Gynecology & Obstetrics\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2025-04-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Gynecology & Obstetrics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1002/ijgo.70108\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"OBSTETRICS & GYNECOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Gynecology & Obstetrics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/ijgo.70108","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"OBSTETRICS & GYNECOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
背景:多囊卵巢综合征(PCOS)是女性最常见的内分泌疾病。许多学者对多囊卵巢综合征的基础和临床研究进行了探索。然而,在PCOS领域的知识结构、文献计量分析和可视化结果等方面的研究还比较缺乏。目的:本研究的主要目的是通过社会网络分析(social network analysis, SNA)和可视化研究,分析PCOS的研究现状,挖掘热点和薄弱环节,为后续研究者提供思路和意见。方法:从Web of Science数据库中收集2018年1月至2022年10月发表的关于PCOS的文献报告。在统计关键词的基础上,生成共词网络,用于计算网络指标。采用描述性统计、共现分析、SNA分析等方法对PCOS的研究热点和研究趋势进行分析。结果:从5828篇论文中共获得唯一关键词9282个(总频次29 847),其中频率大于等于20的高频关键词121个。胰岛素抵抗、高雄激素血症、代谢综合征、超重等关键词在这些关键词中心性排名前五。通过网络计算,将PCOS SNA网络划分为8个簇(C1- c8): C1,复制;C2,发病机理;C3,相关疾病;C4,临床表现;C5,激素调节;C6,临床管理;C7,新的调控因素;C8,基因多态性。集群3、4、6的密度较高,集群1、3、4的度较高。结论:本研究通过SNA和可视化技术揭示了近年来PCOS的研究热点和结构。我们认为多囊卵巢综合征与女性生殖密切相关。虽然多囊卵巢综合征的发病机制尚不清楚,但胰岛素抵抗可能是多囊卵巢综合征的重点研究课题。激素调节是多囊卵巢综合征的关键,多囊卵巢综合征患者需要仔细的临床管理。我们需要对这种疾病的遗传学和新的调控机制进行更多的研究。我们的发现将为研究人员、资助者、政策制定者和临床医生提供可靠和有效的支持。
Theme hotspots and knowledge structure of PCOS: Social network analysis and visualization study based on keywords.
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.
期刊介绍:
The International Journal of Gynecology & Obstetrics publishes articles on all aspects of basic and clinical research in the fields of obstetrics and gynecology and related subjects, with emphasis on matters of worldwide interest.