Advertisement

Scientometrics

, Volume 116, Issue 1, pp 555–568 | Cite as

Highly cited papers in rheumatology: identification and conceptual analysis

  • Veronica Perez-Cabezas
  • Carmen Ruiz-Molinero
  • Ines Carmona-Barrientos
  • Enrique Herrera-Viedma
  • Manuel J. Cobo
  • Jose A. Moral-Munoz
Article
  • 107 Downloads

Abstract

Rheumatology is a broad research area with an extensive background in scientific publications. Thus, the present study aims to identify the highly cited papers in Rheumatology research field, analyzing some aspects such as the documents distribution by years, journals, authors, institutions and countries. Furthermore, a conceptual evolution and a co-word analysis have been performed. In order to carry out this study, the H-Classics methodology, based on widely used H-index, has been used. A total of 317 highly cited papers have been detected from a total amount of 103.175 documents (articles and reviews) indexed in the Rheumatology category of the Web of Science database, from the period 1945–2016. As a result, it is obtained that Arthritis and Rheumatism is the journal with the highest number of documents, with more than half of detected documents. Professor Emery, from the University of Leeds (UK), and professor Felson, from the Boston University (USA), are the authors with more highly cited papers. The University of California (USA) and the University of Stanford (USA) are the main institutional contributors. USA is the leading producer, with more than half of the highly cited papers, but it is interesting to highlight the position reached by Peoples R. China, Mexico and, South Africa when an adjustment index based in the GDP per capita is applied. Osteo-arthritis and monoclonal antibody are the leader topics of this set of documents. The present study shows a useful insight into the development and evolution of the Rheumatology research field, revealing actors that have made the most significant research contribution to its development.

Keywords

h-index Highly cited papers Highly cited journals H-Classics Bibliometrics Rheumatology 

Notes

Acknowledgements

The present study is an extended version of an article (Perez-Cabezas et al. 2017) presented at the 16th International Conference on Scientometrics and Informetrics, Wuhan (China), 16–20 October 2017. The authors want to thanks the support of FEDER funds TIN2013-40658-P and TIN2016-75850-R and University of Cádiz project PR2016-067. On the other hand, they also want to thank the valuable comments received by the 16th International Conference on Scientometrics and Informetrics (ISSI2017) attendees, who have served to improve the extended version of the paper.

References

  1. Alonso, S., Cabrerizo, F. J., Herrera-Viedma, E., & Herrera, F. (2009). h-index: A review focused in its variants, computation and standardization for different scientific fields. Journal of Informetrics, 3(4), 273–289.CrossRefGoogle Scholar
  2. Balazs, E. A., Watson, D., Duff, I. F., & Roseman, S. (1967). Hyaluronic acid in synovial fluid. I. Molecular parameters of hyaluronic acid in normal and arthritic human fluids. Arthritis and Rheumatism, 10(4), 357–376.CrossRefGoogle Scholar
  3. Batlle-Gualda, E., Larraz, P. T., Pons, R. N., & Laserna, C. G. (1998). Investigation in Rheumatology. Analysis of Spanish documents published during 1990-1996 in nine foreign specialty journals. Revista Clinica Espanola, 198(9), 587–595.Google Scholar
  4. Beighton, P., Solomon, L., & Soskolne, C. L. (1973). Articular mobility in an African population. Annals of the Rheumatic Diseases, 32(5), 413–418.CrossRefGoogle Scholar
  5. Bellamy, N., Buchanan, W. W., Goldsmith, C. H., Campbell, J., & Stitt, L. W. (1988). Validation Study of WOMAC: A health status instrument for measuring clinically important patient relevant outcomes to antirheumatic drug therapy in patients with osteoarthritis of the hip or knee. The Journal of Rheumatology, 15(12), 1833–1840.Google Scholar
  6. Bombardier, C., Gladman, D. D., Urowitz, M. B., Caron, D., Chang, C. H., Austin, A., et al. (1992). Derivation of the sledai. A disease activity index for lupus patients. Arthritis and Rheumatism, 35(6), 630–640.CrossRefGoogle Scholar
  7. Brooks, P. M. (2006). The burden of musculoskeletal disease–a global perspective. Clinical Rheumatology, 25(6), 778–781.CrossRefGoogle Scholar
  8. Bywaters, E. G. (1971). Still’s disease in the adult. Annals of the Rheumatic Diseases, 30(2), 121–133.CrossRefGoogle Scholar
  9. Calin, A., Garret, S., Whitelock, H., Kennedy, L. G., Ohea, J., Mallorie, P., et al. (1994). A new approach to defining functional ability in ankylosing-spondylitis–the development of the bath ankylosing-spondylitis functional index. Journal of Rheumatology, 21(12), 2281–2285.Google Scholar
  10. Callon, M., Courtial, J. P., & Laville, F. (1991). Co-word analysis as a tool for describing the network of interactions between basic and technological research: the case of polymer chemistry. Scientometrics, 22(1), 155–205.CrossRefGoogle Scholar
  11. Chen, M., Zhao, M.-H., & Kallenberg, C. G. M. (2011). The impact factor of rheumatology journals: An analysis of 2008 and the recent 10 years. Rheumatology International, 31(12), 1611–1615.CrossRefGoogle Scholar
  12. Cheng, T., & Zhang, X. (2010). Growing trend of Chinaś contribution to the field of rheumatology 2000–2009: A survey of Chinese rheumatology research. The Journal of Rheumatology, 37(11), 2390–2394.CrossRefGoogle Scholar
  13. Cheng, T., & Zhang, G. (2013). Worldwide research productivity in the field of rheumatology from 1996 to 2010: A bibliometric analysis. Rheumatology, 52(9), 1630–1634.CrossRefGoogle Scholar
  14. Cobo, M. J., López-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2011). An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the fuzzy sets theory field. Journal of Infometrics, 5(1), 146–166.CrossRefGoogle Scholar
  15. Cobo, M. J., López-Herrera, A. G. G., Herrera-Viedma, E., & Herrera, F. (2012). SciMAT: A new Science Mapping Analysis Software Tool. Journal of the American Society for Information Science and Technology, 63(8), 1609–1630.CrossRefGoogle Scholar
  16. Downie, W. W., Leatham, P. A., Rhind, V. M., Wright, V., Branco, J. A., & Anderson, J. A. (1978). Studies with pain rating scales. Annals of the Rheumatic Diseases, 37(4), 378–381.CrossRefGoogle Scholar
  17. Forestier, J., & Rotes-Querol, J. (1950). Senile Ankylosing Hyperostosis of the Spine. Annals of the Rheumatic Diseases, 9(4), 321–330.CrossRefGoogle Scholar
  18. Fries, J. F., Spitz, P., Kraines, R. G., & Holman, H. R. (1980). Measurement of patient outcome in arthritis. Arthritis and Rheumatism, 23(2), 137–145.CrossRefGoogle Scholar
  19. Fries, J. F., Spitz, P. W., & Young, D. Y. (1982). The Dimensions of health outcomes–the health assessment questionnaire, disability and pain scales. Journal of Rheumatology, 9(5), 789–793.Google Scholar
  20. Garfield, E. (1977). Introducing citation classics. The human side of scientific reports. Current Comments, 1, 5–7.Google Scholar
  21. Garfield, E. (1987). 100 citation classics from the journal of the American Medical Association. Journal of the American Medical Association, 257, 52–59.CrossRefGoogle Scholar
  22. Garret, S., Jenkinson, T., Kennedy, L. G., Whitelock, H., Gaisford, P., & Calin, A. (1994). A new approach to defining disease status in ankylosing-spondylitis—the bath ankylosing-spondylitis disease-activity index. Journal of Rheumatology, 21(12), 2286–2291.Google Scholar
  23. Gladman, D. D., Urowitz, M. B., Goldsmith, C. H., Fortin, P., Ginzler, E., Gordon, C., et al. (1997). The reliability of the Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index in patients with systemic lupus erythematosus. Arthritis and Rheumatism, 40(5), 809–813.CrossRefGoogle Scholar
  24. Goekoop-Ruiterman, Y. P. M., de Vries-Bouwstra, J. K., Allaart, C. F., van Zeben, D., Kerstens, P. J. S. M., Hazes, J. M. W., et al. (2005). Clinical and radiographic outcomes of four different treatment strategies in patients with early rheumatoid arthritis (the BeSt study): A randomized, controlled. Arthritis and Rheumatism, 52(11), 3381–3390.CrossRefGoogle Scholar
  25. Gregersen, P. K., Silver, J., & Winchester, R. J. (1987). The shared epitope hypothesis. an approach to understanding the molecular genetics of susceptibility to rheumatoid arthritis. Arthritis and Rheumatism, 30(11), 1205–1213.CrossRefGoogle Scholar
  26. Gutiérrez-Salcedo, M., Martínez, M. A., Moral-Munoz, J. A., Herrera-Viedma, E., & Cobo, M. J. (2017). Some bibliometric procedures for analyzing and evaluating research fields. Applied Intelligence, 1–13.Google Scholar
  27. Helmick, C. G., Felson, D. T., Lawrence, R. C., Gabriel, S., Hirsch, R., Kwoh, C. K., et al. (2008). Estimates of the prevalence of arthritis and other rheumatic conditions in the United States. Part I. Arthritis and Rheumatism, 58(1), 15–25.CrossRefGoogle Scholar
  28. Hirsch, J. (2005). An index to quantify an individual’s sceitnific research output. Proceedings of hte National Academy of Sciences, 102, 16569–16572.CrossRefMATHGoogle Scholar
  29. Hodge, D. R., & Lacasse, J. R. (2011). Ranking disciplinary journals with the Google Scholar h-index: A new tool for constructing cases for tenure, promotion, and other professional decisions. Journal of Social Work Education, 47(3), 579–596.CrossRefGoogle Scholar
  30. Kellgren, J. H., & Lawrence, J. S. (1957). Radiological assessment of osteo-arthrosis. Annals of the Rheumatic Diseases, 16(4), 494–502.CrossRefGoogle Scholar
  31. Kellgren, J. H., & Lawrence, J. S. (1958). Osteo-arthrosis and disk degeneration in an urban population. Annals of the Rheumatic Diseases, 17(4), 388–397.CrossRefGoogle Scholar
  32. Lawrence, J. S., Bremner, J. M., & Bier, F. (1966). Osteo-arthrosis–prevalence in population and relationship between symptoms and X-ray changes. Annals of the Rheumatic Diseases, 25(1), 1–24.CrossRefGoogle Scholar
  33. Lawrence, R. C., Felson, D. T., Helmick, C. G., Arnold, L. M., Choi, H., Deyo, R. A., et al. (2008). Estimates of the prevalence of arthritis and other rheumatic conditions in the United States: Part II. Arthritis and Rheumatism, 58(1), 26–35.CrossRefGoogle Scholar
  34. Lorig, K., Chastain, R. L., Ung, E., Shoor, S., & Holman, H. R. (1989). Development and evaluation of a scale to measure perceived self-efficacy in people with arthritis. Arthritis and Rheumatism, 32(1), 37–44.CrossRefGoogle Scholar
  35. Martínez, M. A., Herrera, M., López-Gijón, J., & Herrera-Viedma, E. (2014). H-Classics: Characterizing the concept of citation classics through H-index. Scientometrics, 98(3), 1971–1983.CrossRefGoogle Scholar
  36. Mason, R. M., & Barnes, C. G. (1969). Behcet’s syndrome with arthritis. Annals of the Rheumatic Diseases, 28(2), 95–103.CrossRefGoogle Scholar
  37. Moral-Munoz, J. A., Cobo, M. J., Chiclana, F., Collop, A., & Herrera-Viedma, E. (2016). Analyzing highly cited papers in intelligent transportation systems. IEEE Transactions on Intelligent Transportation Systems, 17(4), 993–1001.CrossRefGoogle Scholar
  38. Pearson, C. M., & Wood, F. D. (1959). Studies of polyarthritis and other lesions induced in rats by injection of mycobacterial adjuvant. I. General clinical and pathologic characteristics and some modifying factors. Arthritis and Rheumatism, 2(5), 440–459.CrossRefGoogle Scholar
  39. Perez-Cabezas, V., Ruiz-Molinero, C., Carmona-Barrientos, I., Herrera-Viedma, E., Cobo, M. J., & Moral-Munoz, J. A. (2017). Analysis of highly cited papers in Rheumatology. In Proceedings of ISSI 2017The 16th International Conference on Scientometrics & Informetrics, Wuhan University, China, 622–631.Google Scholar
  40. Prevoo, M. L. L., Van’T Hof, M. A., Kuper, H. H., Van Leeuwen, M. A., Van De Putte, L. B. A., & Van Riel, P. L. C. M. (1995). Modified disease activity scores that include twenty-eight-joint counts development and validation in a prospective longitudinal study of patients with rheumatoid arthritis. Arthritis and Rheumatism, 38(1), 44–48.CrossRefGoogle Scholar
  41. Redondo, M., Leon, L., Povedano, F. J., Abasolo, L., Perez-Nieto, M. A., & López-Muñoz, F. (2016). A bibliometric study of the scientific publications on patient-reported outcomes in rheumatology. Seminars in Arthritis and Rheumatism, 46(6), 828–833.CrossRefGoogle Scholar
  42. Sakaguchi, Y., Sekiya, I., Yagishita, K., & Muneta, T. (2005). Comparison of human stem cells derived from various mesenchymal tissues: Superiority of synovium as a cell source. Arthritis and Rheumatism, 52(8), 2521–2529.CrossRefGoogle Scholar
  43. Seipel, M. M. O. (2003). Assessing publication for tenure. Journal of Social Work Education, 39(1), 79–88.CrossRefGoogle Scholar
  44. Steere, A. C., Malawista, S. E., Snydman, D. R., Shope, R. E., Andiman, W. A., Ross, M. R., et al. (1977). An epidemic of oligoarticular arthritis in children and adults in three connecticut communities. Arthritis and Rheumatism, 20(1), 7–17.CrossRefGoogle Scholar
  45. The World Bank. (2016). GDP (current US$). The World Bank Data. https://data.worldbank.org/indicator/NY.GDP.MKTP.CD.
  46. Vargas-Quesada, B., Chinchilla-Rodríguez, Z., & Rodríguez, N. (2017). Identification and visualization of the intellectual structure in graphene research. Frontiers in Research Metrics and Analytics, 2, 7.CrossRefGoogle Scholar
  47. Wolfe, F., Mitchell, D. M., Sibley, J. T., Fries, J. F., Bloch, D. A., Williams, C. A., et al. (1994). The mortality of rheumatoid arthritis. Arthritis and Rheumatism, 37(4), 481–494.CrossRefGoogle Scholar
  48. Wolfe, F., Ross, K., Anderson, J., Russell, I. J., & Hebert, L. (1995). The prevalence and characteristics of fibromyalgia in the general population. Arthritis and Rheumatism, 38(1), 19–28.CrossRefGoogle Scholar
  49. Zyoud, S. H., Al-Jabi, S. W., & Sweileh, W. M. (2015). Worldwide research productivity of paracetamol (acetaminophen) poisoning: A bibliometric analysis (2003–2012). Human and Experimental Toxicology, 34(1), 12–23.CrossRefGoogle Scholar

Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2018

Authors and Affiliations

  • Veronica Perez-Cabezas
    • 1
  • Carmen Ruiz-Molinero
    • 1
  • Ines Carmona-Barrientos
    • 1
  • Enrique Herrera-Viedma
    • 2
  • Manuel J. Cobo
    • 3
  • Jose A. Moral-Munoz
    • 1
    • 4
  1. 1.Department of Nursing and PhysiotherapyUniversity of CádizCádizSpain
  2. 2.Department of Computer Science and Artificial IntelligenceUniversity of GranadaGranadaSpain
  3. 3.Department of Computer Science and EngineeringUniversity of CádizCádizSpain
  4. 4.Institute of Research and Innovation in Biomedical Sciences of the Province of Cádiz (INiBICA), University of CádizCádizSpain

Personalised recommendations