Bibliometric Analysis of The 40 Years Literature On Vertebral Fractures With Science Mapping Method

Year 2024, Volume: 8 Issue: 3, 244 - 255, 30.12.2024

Ahmet Karaoglu

https://doi.org/10.30565/medalanya.1518860

Abstract

Each year, over 1.5 million individuals in the United States are diagnosed with vertebral compression fractures. The concept of bibliometrics pertains to the analysis of bibliographic data. The examination and visualization of the literature within a scientific discipline or its subcategories is referred to as science mapping. This study represents a comprehensive analysis of the literature on vertebral fractures. In our research, the Web of Science database was utilized for analyses, encompassing the period from 1980 to 2022. The analyses were divided into four categories: performance analysis, keyword analysis, thematic analysis, and co-citation network analysis. Word Cloud, Frequency Table, Trend Topics, and Co-occurrence Networks were examined. Thematic Maps and Thematic Evolution Maps were also constructed. Furthermore, a co-citation network analysis of articles was conducted. The analyzed articles were authored by 9,020 researchers. The annual increase in the number of publications was recorded as 9.54%. The average number of citations per document was 44.05. Approximately 18.7% of the articles were published through international collaborations, with Europe standing out prominently in this regard. Genant HK was identified as the author with the highest h- and g-indices. The most active institution was the University of California, San Francisco. The most frequently used keywords included Vertebral Fracture, Osteoporosis, and Bone Mineral Density. Over the past 40 years, the scientific literature on spinal fractures has been analyzed through science mapping. The developmental dynamics of this field have been identified.

Keywords

Bibliometrics, Science Mapping, Vertebral Fractures, Web of Science.

Supporting Institution

yok

Project Number

yok

Bilimsel Haritalama Yöntemiyle Vertebral Kırıklara İlişkin 40 yıllık Literatürün Bibliyometrik Analizi

Abstract

Amerika Birleşik Devletleri'nde her yıl 1,5 milyondan fazla kişiye vertebral kompresyon kırığı tanısı konmaktadır. Bibliyometri kavramı bibliyografik verilerin incelenmesidir. Bir bilimsel disiplinin veya onun alt kategorisine ait literatürün analizi ve görselleştirilmesi bilim haritalaması olarak tanımlanmaktadır. Bu çalışma vertebra kırıkları ile ilgili literatürün kapsamlı bir analizidir. Araştırmamızda analizler için Web of Science kullanılmıştır. Çalışmamız 1980'den 2022'ye kadar olan zaman dilimini kapsamaktadır. Analizler; performans, anahtar kelime, tematik ve ortak atıf ağı analizleri olmak üzere dört bölümden oluşmaktadır. Kelime Bulutu ve Frekans Tablosu, Trend Konuları ve Birlikte Oluşum Ağı analiz edilmiştir. Tematik Harita ve Tematik Gelişim Haritası oluşturulmuştur. Makale Ortak Alıntı Ağı analizi gerçekleştirilmiştir. Analiz edilen makaleler 9.020 yazar tarafından yazılmıştır. Makale sayısındaki yıllık artış ise %9,54 oldu. Belge başına ortalama alıntı sayısı 44,05'tir. Makalelerin yaklaşık %18,7'si uluslararası işbirliği yoluyla yayınlanmıştır. Uluslararası işbirliği açısından Avrupa özellikle öne çıkıyor. Genant HK en yüksek h ve g-indeksine sahip yazardır. En aktif kurum San Francisco'daki Kaliforniya Üniversitesi'dir. En çok tekrarlanan anahtar kelimeler Vertebral Kırık, Osteoporoz, Kemik Mineral Yoğunluğu'dur. Omurga kırıklarına ilişkin son 40 yıllık literatür bilimsel haritalamayla analiz edilmiştir. Konunun gelişim dinamikleri belirlenmiştir.

Keywords

Bibliyometri, Bilim Haritalaması, Vertebral Kırıklar, Web of Science.

Project Number

yok

References

• 1. Ferreira ML, March L. Vertebral fragility fractures - How to treat them? Best Pract Res Clin Rheumatol. 2019;33(2):227–35. doi: 10.1016/j.berh.2019.03.017.
• 2. Ralston SH, Fraser J. Diagnosis and management of osteoporosis. Practitioner. 2015;259(1788):15-9, 2. PMID: 26882774.
• 3. Sözen T, Özışık L, Başaran NÇ. An overview and management of osteoporosis. Eur J Rheumatol. 2017;4(1):46–56. doi: 10.5152/eurjrheum.2016.048.
• 4. Lau E, Ong K, Kurtz S, Schmier J, Edidin A. Mortality following the diagnosis of a vertebral compression fracture in the Medicare population. J Bone Joint Surg Am. 2008;90(7):1479–86. doi: 10.2106/JBJS.G.00675.
• 5. Mingers J, Leydesdorff L. A review of theory and practice in scientometrics. Eur J Oper Res. 2015;246(1):1–19. doi: 10.1016/j.ejor.2015.04.002.
• 6. Börner K, Rouse WB, Trunfio P, Stanley HE. Forecasting innovations in science, technology, and education. Proc Natl Acad Sci U S A. 2018;115(50):12573-12581. doi: 10.1073/pnas.1818750115.
• 7. Fortunato S, Bergstrom CT, Börner K, Evans JA, Helbing D, Milojević S, et al. Science of science. Science. 2018;359(6379):eaao0185. doi: 10.1126/science.aao0185.
• 8. Chhabra HS, Phadke V, Manghwani J, El-Sharkawi M, Butler JS, Benneker LM, et al. An Assessment of the World’s Contribution to Spine Trauma Care: A Bibliometric Analysis of Classifications and Surgical Management; An AO Spine Knowledge Forum Trauma Initiative. Glob spine J. 2024;14(3):1061–9. doi: 10.1177/21925682231205104.
• 9. Mavrovounis G, Makris M, Demetriades AK. Traumatic spinal cord and spinal column injuries: A bibliometric analysis of the 200 most cited articles. J craniovertebral junction spine. 2023;14(4):346–64. doi: 10.4103/jcvjs.jcvjs_97_23.
• 10. Pessin VZ, Santos CAS, Yamane LH, Siman RR, Baldam R de L, Júnior VL. A method of Mapping Process for scientific production using the Smart Bibliometrics. MethodsX. 2023;11:102367. doi: 10.1016/j.mex.2023.102367.
• 11. Giorgi FM, Ceraolo C, Mercatelli D. The R Language: An Engine for Bioinformatics and Data Science. Life (Basel, Switzerland). 2022;12(5):648 doi: 10.3390/life12050648.
• 12. Masic I. The Most Influential Scientist in the Development of Medical informatics (17): Eugene Garfield. Acta Inform Med. 2017;25(2):145. doi: 10.5455/aim.2017.25.145-145.
• 13. Kreiner G. The Slavery of the h-index-Measuring the Unmeasurable. Front Hum Neurosci. 2016;10:556. doi: 10.3389/fnhum.2016.00556.
• 14. Shah FA, Jawaid SA. The h-Index: An Indicator of Research and Publication Output. Pakistan J Med Sci. 2023;39(2):315–6. doi: 10.12669/pjms.39.2.7398.
• 15. Egghe L. Theory and practise of the g-index. Scientometrics. 2006;69(1):131–52. doi: 10.1007/s11192-006-0144-7.
• 16. Link TM. Obituary for Professor Harry K. Genant, MD. Eur Radiol. 2021;31(6):4416–7. doi: 10.1007/s00330-021-07822-z.
• 17. Osteoporosis International [Internet]. 2024. Available from: https://link.springer.com/journal/198
• 18. Journal of Bone and Mineral Research [Internet]. 2024. Available from: https://academic.oup.com/jbmr#google_vignette
• 19. Genant HK, Wu CY, van Kuijk C, Nevitt MC. Vertebral fracture assessment using a semiquantitative technique. J bone Miner Res Off J Am Soc Bone Miner Res. 1993;8(9):1137–48. doi: 10.1002/jbmr.5650080915.
• 20. Lindsay R, Silverman SL, Cooper C, Hanley DA, Barton I, Broy SB, et al. Risk of new vertebral fracture in the year following a fracture. JAMA. 2001;285(3):320–3. doi: 10.1001/jama.285.3.320.
• 21. Black DM, Cummings SR, Karpf DB, Cauley JA, Thompson DE, Nevitt MC, et al. Randomised trial of effect of alendronate on risk of fracture in women with existing vertebral fractures. Fracture Intervention Trial Research Group. Lancet. 1996;348(9041):1535–41. doi: 10.1016/s0140-6736(96)07088-2.
• 22. Schousboe JT, Bauer DC, Nyman JA, Kane RL, Melton LJ, Ensrud KE. Potential for bone turnover markers to cost-effectively identify and select post-menopausal osteopenic women at high risk of fracture for bisphosphonate therapy. Osteoporos Int. 2007;18(2):201-10. doi: 10.1007/s00198-006-0218-7.
• 23. Otto E, Culakova E, Meng S, Zhang Z, Xu H, Mohile S, et al. Overview of Sankey flow diagrams: Focusing on symptom trajectories in older adults with advanced cancer. J Geriatr Oncol. 2022;13(5):742–6. doi: 10.1016/j.jgo.2021.12.017.
• 24. Roux C, Fechtenbaum J, Kolta S, Briot K, Girard M. Mild prevalent and incident vertebral fractures are risk factors for new fractures. Osteoporos Int. 2007;18(12):1617-24. doi: 10.1007/s00198-007-0413-1.
• 25. Kanis JA, Devogelaer JP, Gennari C. Practical guide for the use of bone mineral measurements in the assessment of treatment of osteoporosis: a position paper of the European foundation for osteoporosis and bone disease. The Scientific Advisory Board and the Board of National Societies. Osteoporos Int. 1996;6(3):256-61. doi: 10.1007/BF01622743.
• 26. Sone T, Ito M, Fukunaga M, Tomomitsu T, Sugimoto T, Shiraki M, et al. The effects of once-weekly teriparatide on hip geometry assessed by hip structural analysis in postmenopausal osteoporotic women with high fracture risk. Bone. 2014;64:75–81. doi: 10.1016/j.bone.2014.04.004.
• 27. Mazziotti G, Sorvillo F, Piscopo M, Cioffi M, Pilla P, Biondi B, et al. Recombinant human TSH modulates in vivo C-telopeptides of type-1 collagen and bone alkaline phosphatase, but not osteoprotegerin production in postmenopausal women monitored for differentiated thyroid carcinoma. J Bone Miner Res. 2005;20(3):480-6. doi: 10.1359/JBMR.041126.
• 28. Radhakrishnan S, Erbis S, Isaacs JA, Kamarthi S. Novel keyword co-occurrence network-based methods to foster systematic reviews of scientific literature. PLoS One. 2017;12(3):e0172778. doi: 10.1371/journal.pone.0172778.
• 29. Fink HA, Milavetz DL, Palermo L, Nevitt MC, Cauley JA, Genant HK, et al. What proportion of incident radiographic vertebral deformities is clinically diagnosed and vice versa? J bone Miner Res Off J Am Soc Bone Miner Res. 2005;20(7):1216–22. doi: 10.1359/JBMR.050314.
• 30. Casez P, Uebelhart B, Gaspoz J-M, Ferrari S, Louis-Simonet M, Rizzoli R. Targeted education improves the very low recognition of vertebral fractures and osteoporosis management by general internists. Osteoporos Int. 2006;17(7):965-70. doi: 10.1007/s00198-005-0064-z.
• 31. Li Y-C, Chen H-H, Horng-Shing Lu H, Hondar Wu H-T, Chang M-C, Chou P-H. Can a Deep-learning Model for the Automated Detection of Vertebral Fractures Approach the Performance Level of Human Subspecialists? Clin Orthop Relat Res. 2021;479(7):1598–612. doi: 10.1097/CORR.0000000000001685.
• 32. Zhang J, Liu J, Liang Z, Xia L, Zhang W, Xing Y, et al. Differentiation of acute and chronic vertebral compression fractures using conventional CT based on deep transfer learning features and hand-crafted radiomics features. BMC Musculoskelet Disord. 2023 Mar;24(1):165. doi: 10.1186/s12891-023-06281-5.
• 33. Anastasilakis AD, Polyzos SA, Makras P, Aubry-Rozier B, Kaouri S, Lamy O. Clinical Features of 24 Patients With Rebound-Associated Vertebral Fractures After Denosumab Discontinuation: Systematic Review and Additional Cases. J Bone Miner Res. 2017;32(6):1291-6. doi: 10.1002/jbmr.3110.
• 34. Cummings SR, Ferrari S, Eastell R, Gilchrist N, Jensen J-EB, McClung M, et al. Vertebral Fractures After Discontinuation of Denosumab: A Post Hoc Analysis of the Randomized Placebo-Controlled FREEDOM Trial and Its Extension. J Bone Miner Res. 2018;33(2):190-8. doi: 10.1002/jbmr.3337.
• 35. Schöggl J-P, Stumpf L, Baumgartner RJ. The narrative of sustainability and circular economy-A longitudinal review of two decades of research. Resour Conserv Recycl. 2020;163:105073. doi: 10.1016/j.resconrec.2020.105073.
• 36. Nasir A, Shaukat Dar K, Hameed IA, Luo S, Mahboob T, Iqbal F, et al. A Bibliometric Analysis of Corona Pandemic in Social Sciences: A Review of Influential Aspects and Conceptual Structure. IEEE Access. 2020;8:133377–402. doi: 10.1109/ACCESS.2020.3008733.