Science Mapping of “Trauma Surgery” by Co‑Word Analysis and Thematic Clustering in MEDLINE

Document Type : Original Article


1 Trauma Research Center, Baqiyatallah University of Medical Sciences,Tehran, Iran

2 1Health Management Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran

3 Department of Surgery, Medical Faculty, Baqiyatallah University of Medical Sciences, Tehran, Iran



Background: Trauma surgery has an interdisciplinary nature among the surgical specialties, and trauma surgeons are required to identify its
related scientific fields to acquire the needed skills in controlling the injuries. This study was conducted to investigate the science mapping of
trauma surgery based on the bibliographic data of MEDLINE. Methodology: Based on the bibliographic data from the MEDLINE database,
the visualizing techniques of bibliometric networks and all the scientific products of the trauma surgery realm indexed at MEDLINE from
2008 to 2017 were investigated. Data analysis was performed using co‑word analysis and cluster analysis using the VOSviewer. Results: The
growth trend of scientific productions in the field of trauma surgery has been on the rise in the past 10 years. The keyword “trauma,” followed
by “osteoporosis,” “fracture outcome,” “trauma surgery,” and “mortality” had respectively the highest frequency. The results of cluster analysis
identified the most important basic research subjects of trauma surgery published in MEDLINE in the past 10 years and categorized them into
five clusters. Trauma surgery field had a close relationship with the field of orthopedics, basic studies, and laboratory research in comparison
with its clinical domains. Conclusion: We attempted to identify the vastness of the knowledge subjects of trauma surgery and to conduct
educational research, and technological planning so that the managers and stakeholders can trace the path of future scientific activities in the
field of trauma surgery. The identification of this important realm and provision of the required information on the core issues for the users
can be facilitated by drawing up a science map and visualizing the main traumatic sciences.


1. Ball CG. Damage control resuscitation: History, theory and technique. Can J Surg 2014;57:55‑60.
2. Moore EE. Trauma surgery: Is it time for a facelift? Ann Surg 2004;240:563‑4.
3. Peitzman AB. Status of trauma and acute care surgery in the United States. Ulus Travma Acil Cerrahi Derg 2008;14:1‑4.
4. Spain DA, Miller FB. Education and training of the future trauma surgeon in acute care surgery: Trauma, critical care, and emergency surgery. Am J Surg 2005;190:212‑7.
5. Galante JM, Phan HH, Wisner DH. Trauma surgery to acute care surgery: Defining the paradigm shift. J Trauma 2010;68:1024‑31.
6. Ball CG, Das D, Roberts DJ, Vis C, Kirkpatrick AW, Kortbeek JB, et al. The evolution of trauma surgery at a high‑volume Canadian centre: Implications for public health, prevention, clinical care, education and recruitment. Can J Surg 2015;58:19‑23.
7. Jinescu G, Lica I, Beuran M. Traumatic colon injuries – Factors that influence surgical management. Chirurgia (Bucur) 2013;108:652‑8.
8. Chico‑Fernández M, Terceros‑Almanza LL, Mudarra‑Reche CC. Innovation and new trends in critical trauma disease. Med Intensiva 2015;39:179‑88.
9. Pretz JL, Magnus D, Spain DA. Emergency innovation: Implications for the trauma surgeon. J Trauma 2009;67:1443‑7.
10. Velmahos GC, Alam HB. Acute care surgery: The natural evolution of trauma surgery. Scand J Surg 2010;99:59‑60.
11. Makkizadeh F, Hazeri A, Hosininasab SH, Soheili F. Thematic analysis and scientific mapping of papers related to depression therapy in PubMed. J Health Adm 2016;19:51‑63.
12. Yao Q, Chen K, Yao L, Lyu PH, Yang TA, Luo F, et al. Scientometric trends and knowledge maps of global health systems research. Health Res Policy Syst 2014;12:26.
13. Börner K, Scharnhorst A. Visual conceptualizations and models of science. J Informetr 2009;3:161‑72.
14. Sedighi M. Using co‑word analysis method in mapping of the structure of scientific fields (Case Study: The Field of Informetrics). Iran Res Inst Sci Technol 2015;30:373‑96.
15. Xiuwen Chena B, Chena J, Wua D, Xiea Y, Lic J. Mapping the research trends by co‑word analysis based on keywords from funded project. Procedia Comput Sci 2016;91:547‑55.
16. Neff MW, Corley EA. 35 Years and 160,000 Articles: A bibliometric exploration of the evolution of ecology. Scientometrics 2009;80:657‑82.
17. Porter A, Rafols L. Is science becoming more interdisciplinary? Measuring and mapping six research fields over time. Scientometrics 2009;81:719‑45.
18. VanEck NJ. Waltman L. Visualizing bibliometric networks. In: Ding Y, Rousseau R, Wolfram D, ediotrs. Measuring scholarly impact: Methods and practice. Q J Res Addict 2017;11:285‑320.
19. Börner K, Klavans R, Patek M, Zoss AM, Biberstine JR, Light RP, et al. Design and update of a classification system: The UCSD map of science. PLoS One 2012;7:e39464.
20. VanEck NJ. Waltman L. Text mining and visualization using VOSviewer. ISSI Newsletter 2011;7:50‑4.
21. VanEck NJ. Waltman L. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 2010;4:523‑38.
22. Lee S. A study on research trends in public library research in Korea using keyword networks. Libri 2016;66:263‑74.
 23. Hu J, Yin Z. Research patterns and trends of recommendation system in China using co‑word analysis. Inform Process Manage 2015;51:329‑39. 24. Hu C, Hu SL, Liu H. A co‑word analysis of library and information science in China. Scientometrics 2013;97:369‑82.
25. Makkizadeh F, Hazeri A. Thematic analysis and scientific mapping of papers related to addiction in medline. J Health Adm 2016;19:51‑63.