Global research status of pathological scar reported over the period 2001-2021: A 20-year bibliometric analysis

Abstract

Pathological scar is a classic problem in plastic and reconstructive surgery. Although the researches on pathological scar have been conducted for decades, the way to go to address this thorny problem still remains challenging. To the best of our knowledge, few bibliometric analysis concerning pathological scar have been reported. In this study, we set out to employ bibliometric and visual analysis to offer research status and trends of pathological scar over the period 2001-2021. All publications covering pathological scar during 2001-2021 were retrieved and extracted from the Web of Science database. We applied VOSviewer software to evaluate the keywords and research hotpots, and the online tool (http://bibliometric.com/) was used to carried out the publication trends analysis. A total of 2221 pathological scar-related articles were identified over the period 2001-2021. China is the country which had the largest volume of publications (819, 36.87%), followed by the United States (416, 18.73%), Japan (144, 6.48%), Korea (142, 6.39%), and England (118, 5.31%). Among the institutions and journals, Shanghai Jiao Tong University (167) and Wound Repair and Regeneration (85) accounted for the most papers related to pathological scar, respectively. Professor Bayat A, who had the most citation frequency (2303), made great contribution in pathological scar field. "Fibroblast", "expression", and "proliferation" were identified as the pathological scar research hotspot through analysis of the keywords. In terms of publication, China ranked first all over the world, but the numbers of publication are inconsistent with the citation frequency, ranking first and second, respectively. Shanghai Jiao Tong University and journal Wound Repair and Regeneration stand for the highest level of research in this field to a certain extent. In the early stage, the research focus was mainly on the prevention, treatment, and risk factors for recurrence of pathological scar from cases. In the later stage, the research focus was on the comprehensive management, in which the mechanism research was in-depth to the molecular and gene level.

Keywords: bibliometric analysis; hypertrophic scar; keloid; keywords; pathological scar; research hotspots.

FIGURE 1

Flow diagram of literature selection and screening in this study

FIGURE 2

The number of annual publications in pathological scar from 2001 to 2021

FIGURE 3

The curves of growth trends of publications related to pathological scar (A) Global; (B) China; (C) the United States; (D) Japan

FIGURE 4

The contributions of different countries/regions to the research field concerning pathological scar. (A) The growth trends of the top 10 countries/regions in pathological scar during 2001–2021. (B) The number of publications, citation frequency (×0.05), and H‐index (×10) of the top 10 countries or regions

FIGURE 5

The cooperation of countries/regions in pathological scar research during 2001–2021

FIGURE 6

The contributions and cooperation of different institutions. (A) Distribution of top 10 institutions focusing on pathological scar; (B) The cooperation of institutions in pathological scar, and the circle with a large size represented the institution that published more articles; (C) Distribution of institutions was presented according to the appearance for the average time

FIGURE 7

The top 10 journals publishing research on pathological scar

FIGURE 8

The analysis of keywords in publications of pathological scar. (A) Mapping of the keywords in the area of pathological scar. The words were divided into four cluster in accordance with different colours generated by default: cluster 1 (mechanism‐related research, blue), cluster 2 (clinical research, red), cluster 3 (diagnostic research, green), and cluster 4 (gene‐related research, yellow). The circle with a large size represented the keywords that appeared at a high frequency; (B) Distribution of keywords was presented according to the appearance for the average time. The blue colour represented early appearance and yellow colour recent appearance. Two keywords cooccurred if they both occurred on the same line in the corpus file. The smaller the distance between two keywords, the larger the number of cooccurrences of the keywords