Global Trends in Diabetic Foot Research (2004-2023): A Bibliometric Study Based on the Scopus Database

Abstract

Diabetic foot is one of the leading complications of diabetes mellitus that affects millions of people around the world and involves the presence of ulcers, infections, tissue destruction, and loss of sensation and can even lead to limb amputation. This research explores trends in diabetic foot global research through a bibliometric analysis of publications indexed in Scopus in the period 2004-2023. A total of 7136 documents were analysed using Excel, Python, Biblioshiny, and VOSviewer. Scientific production has multiplied by a factor of 6.6 from the first to the last year analysed. Armstrong D.G. is the most productive and cited author. China is the most productive country, and the United States is the most cited. The most productive journal is the International Journal of Lower Extremity Wounds, and the most cited journal is Diabetes Care. Research on diabetic foot is mainly focused on the complications of diabetes mellitus; the treatment and healing of wounds; infections; and epidemiology and patient care. Infections and antibiotic treatment are emerging topics, while deep learning and machine learning are among the niche topics in this area of knowledge. The present study allows us to identify current trends and future directions of research in diabetic foot.

Keywords: Scopus; bibliometric analysis; diabetic foot; research trends.

Figure 1

Flowchart of data filtering process and publications excluded.

Figure 2

Annual growth of the typologies of papers on diabetic foot in Scopus from 2004 to 2023.

Figure 3

Distribution of citations received according to document type over time.

Figure 4

Top 10 most productive authors over time in the field of diabetic foot (2004–2023).

Figure 5

Collaboration networks between authors: (a) collaboration network of authors with 10 or more published documents and a maximum of 10 signatures per article on diabetic foot showing the 14 clusters generated and (b) collaboration network via overlay visualisation representing the production of these authors over time. The colours of the nodes, explained via a colour bar in the corner, show the current production of these authors, with yellow representing the most recent publications and blue representing the less recent ones, throughout the period of analysis. The node size represents the output of each author, and the thickness of the lines indicates the strength of association between authors.

Figure 6

Publications by countries in the field of diabetic foot (2004–2023). (a) Country production over time; (b) collaboration between countries according to the affiliation of the corresponding author (SCPs: Single-Country Publications; MCPs: Multiple-Country Publications).

Figure 6

Publications by countries in the field of diabetic foot (2004–2023). (a) Country production over time; (b) collaboration between countries according to the affiliation of the corresponding author (SCPs: Single-Country Publications; MCPs: Multiple-Country Publications).

Figure 7

Network of international collaboration between countries. It shows the collaboration of 52 countries with at least 20 documents published on the world map. Each node represents a country/region, and each line represents a link between two countries/regions. The size of each node represents the number of documents, and the thickness of each line represents the strength of the link.

Figure 8

Most relevant keywords: (a) 50 index keywords (IDs); (b) 50 author keywords (DEs).

Figure 9

Co-occurrence networks of index keywords (IDs) of the 1413 IDs that appeared at least 15 times. (a) Co-occurrence network and (b) co-occurrence temporal overlap network maps. The colours of the nodes represent the ID groups. Each node represents a keyword and its co-occurrence size. Each line represents a link between two keywords and their thickness, that is, the strength of the link. In the co-occurrence time overlap map, the colour of each node represents the average publication year. The lighter colours show greater relevance of the terms, and the darker ones show greater age in the period analysed, 2004–2023.

Figure 10

Co-occurrence networks of author keywords (DEs) of the 156 DEs that appeared at least 15 times. (a) Co-occurrence network and (b) co-occurrence temporal overlap network maps. The colours of the nodes represent the DE groups. Each node represents a keyword and its co-occurrence size. Each line represents a link between two keywords and their thickness, that is, the strength of the link. In the co-occurrence time overlap map, the colour of each node represents the average publication year. The lighter colours show greater relevance of the terms, and the darker ones show greater age in the period analysed, 2004–2023.

Figure 11

Maps of the thematic evolution by decades of research on diabetic foot according to the author keywords generated through the Walktrap grouping logarithm with 500 terms: (a) 2004–2013 period; (b) 2014–2023 period.