A bibliometric analysis of articles published in the field of trauma in Emergency Medicine journals

Abstract

Background: There is no bibliometric study on trauma in emergency medicine.Objectives: To evaluate the bibliometric parameters of the articles in the field of trauma published in emergency medicine (EM) journals and perform machine learning-based analyses, including current approaches, variability in the subject selection, and impact power and sentiment analysis of publications in this field.Methods: We searched for articles published in EM journals by searching the SCOPUS database with the keyword "trauma" between January 1, 2012, and December 31, 2021. We created the database of the study from the bibliometric parameters of these articles. We downloaded the study data to the artificial intelligence database using computer programs and performed the analysis.Results: We included 8528 articles contributed by 33572 authors. The most used keywords were trauma (n=1887), mortality (n=285), and injury (n=269). Trend topic: delinquency, pulmonary contusion, and NF-κB at the beginning of the study, recently COVID-19, pandemic, and coronavirus. In correlation analysis, we found a correlation between the number of citations and the author's h-indexes (r=0.916, p=0.001), between the number of citations and the number of articles (r=0.698, p=0.001), between the number of articles and the year (r=0.921, p=0.001), between the number of articles and the total number of citations per article (r=-0.909, p=0.001), and between the number of articles and year (r=0.921, p=0.001). We found that EPs had negative sentiments about trauma (n=6435, 75.46%).Conclusion: This study includes a cross-sectional review of trauma publications in EM and offers EPs a new perspective on trauma studies.

Keywords

• trauma
• bibliometric
• emergency medicine