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Hotspots and Trends in Research on Postpartum Pelvic Floor Dysfunction: A Visualization and Bibliometric Analysis
Qianqian Zhou1, Yiwen Jiang2, Qing Cai2
1School of Nursing and Health Management, Shanghai University of Medicine & Health Sciences, 279 Zhouzhu Highway, Shanghai, China.
This bibliometric analysis reveals increasing research on postpartum pelvic floor dysfunction (PFD). Key areas include stress urinary incontinence, anal incontinence, and delivery modes, highlighting the need for global collaboration and AI advancements.
Area of Science:
- Obstetrics & Gynecology
- Rehabilitation Medicine
- Bibliometrics
Background:
- Postpartum pelvic floor dysfunction (PFD) is a prevalent condition affecting women after childbirth.
- Despite numerous studies, a systematic quantification and summary of postpartum PFD research are lacking.
- This study addresses this gap by analyzing research trends from 2005-2024.
Purpose of the Study:
- To systematically analyze the research status, hotspots, and emerging trends in postpartum PFD using bibliometric methods.
- To provide a comprehensive overview of the scientific landscape of postpartum PFD research over two decades.
Main Methods:
- Bibliometric analysis of studies on postpartum PFD from the Web of Science Core Collection (2005-2024).
- Visualization and analysis of authors, countries, institutions, references, and keywords using CiteSpace software.
Main Results:
- A total of 1149 publications were identified, showing an increasing trend over the past two decades.
- International Urogynecology Journal, University of Oslo, and Kari Bø were identified as leading journal, institution, and author, respectively.
- Research hotspots include stress urinary incontinence, anal incontinence, chronic pain, mode of delivery, and transperineal ultrasound.
Conclusions:
- This bibliometric analysis offers insights into current research hotspots and trends in postpartum PFD.
- Future research should prioritize global collaboration, multidisciplinary studies, and the integration of AI in diagnostics and therapeutics.
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