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Theme hotspots and knowledge structure of PCOS: Social network analysis and visualization study based on keywords
Yanjun Wang1, Jinli Ding1, Yuguo Min2
1Reproductive Medicine Center, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.
Summary
Polycystic ovary syndrome (PCOS) research highlights insulin resistance as a key area. This study used bibliometric analysis to map PCOS research trends, identifying critical topics like hormone regulation and clinical management.
Area of Science:
- Endocrinology
- Reproductive Medicine
- Bibliometrics
Background:
- Polycystic ovary syndrome (PCOS) is a prevalent endocrine disorder in women.
- Existing research lacks comprehensive bibliometric analysis and knowledge structure mapping.
- Understanding PCOS research trends is crucial for future scientific endeavors.
Purpose of the Study:
- To analyze the current research landscape of PCOS.
- To identify research hotspots and knowledge gaps using social network analysis (SNA).
- To provide insights for future PCOS research directions.
Main Methods:
- Collected 5828 PCOS-related papers from Web of Science (Jan 2018-Oct 2022).
- Utilized keyword co-occurrence analysis and SNA to map research structure.
- Analyzed descriptive statistics, network indicators, and keyword centrality.
Main Results:
- Identified 9282 unique keywords, with 121 high-frequency terms.
- Insulin resistance, hyperandrogenemia, metabolic syndrome, and overweight were central keywords.
- SNA revealed eight distinct research clusters, including pathogenesis, clinical management, and genetics.
Conclusions:
- PCOS research is strongly linked to female reproduction and hormone regulation.
- Insulin resistance emerges as a critical focus area in PCOS pathogenesis.
- Further research is needed on PCOS genetics and novel regulatory mechanisms.
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