Advances in stem cells treatment of diabetic wounds: A bibliometric analysis via CiteSpace

Author:

Ma Ke123ORCID,Luo Chao4ORCID,Du Mindong25ORCID,Wei Qiang1ORCID,Luo Qianxuan1ORCID,Zheng Li23ORCID,Liao Mingde1ORCID

Affiliation:

1. Department of Plastic & Cosmetic Surgery The First Affiliated Hospital of Guangxi Medical University Nanning China

2. Guangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration The First Affiliated Hospital of Guangxi Medical University Nanning China

3. Pharmaceutical College Guangxi Medical University Nanning China

4. Shanghai Mental Health Center Shanghai Jiao Tong University, School of Medicine Shanghai China

5. Department of Orthopaedics Trauma and Hand Surgery The First Affiliated Hospital of Guangxi Medical University Nanning China

Abstract

AbstractDiabetes is a chronic medical condition that may induce complications such as poor wound healing. Stem cell therapies have shown promise in treating diabetic wounds with pre‐clinical and clinical studies. However, little bibliometric analysis has been carried out on stem cells in the treatment of diabetic wounds. In this study, we retrieved relevant papers published from January 1, 2003, to December 31, 2023, from Chinese and English databases. CiteSpace software was used to analyze the authors, institutions, and keywords by standard bibliometric indicators. Our analysis findings indicated that publications on stem cells in the treatment of diabetic wounds kept increasing. The most prolific author was Qian Cai (n = 7) and Mohammad Bayat (n = 16) in Chinese and English databases, respectively. Institutions distribution analysis showed that Chinese institutions conducted most publications, and the most prolific institution was the Chinese People's Liberation Army General Hospital (n = 9) and Shahid Beheshti University of Medical Sciences (n = 17) in Chinese and English databases, respectively. The highest centrality keyword in Chinese and English databases was “wound healing” (0.54) and “in vitro” (0.13), respectively. There were 8 and 11 efficient and convincing keyword clusters produced by a log‐likelihood ratio in the Chinese and English databases, respectively. The strongest burst keyword was “exosome” (strength 3.57) and “endothelial progenitor cells” (strength 7.87) in the Chinese and English databases, respectively. These findings indicated a direction for future therapies and research on stem cells in the treatment of diabetic wounds.

Funder

Natural Science Foundation of Guangxi Province

Publisher

Wiley

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