Spinal Research — A Field in Need of Standardization

Khan, Danyal Z.; Davies, Benjamin; Kotter, Mark R N

doi:10.3899/jrheum.191225

Cited by 11 publications

(10 citation statements)

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“…As we have published previously [ 7 ], owing to the difficulties in indexing DCM literature, the results presented here are based upon an extensive hand search of the literature (title and abstract only). Whilst this may introduce an element of subjectivity – the reviewers must decide which papers meet the pre-established criteria and which do not and this is not always clear – this was the preferred approach to ensure a more comprehensive representation of the field.…”

Section: Discussionmentioning

confidence: 99%

“…Their findings are fundamentally underpinned on the studies that they identify. Within the field of DCM, there is inconsistent disease terminology, with an absence of index terms or codes [ 7 ], which makes literature searching extremely inefficient. For this reason, and to support work by the Myelopathy.org charity, a hand indexed database of primary clinical articles has been maintained.…”

Section: Methodsmentioning

confidence: 99%

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Research activity amongst DCM research priorities

et al. 2021

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Introduction Degenerative cervical myelopathy (DCM) is a progressive neurodegenerative disorder. DCM is common (estimated prevalence, 2% of adults) and significantly impacts quality of life. The AO Spine RECODE-DCM (Research Objectives and Common Data Elements in DCM) project has recently established the top research priorities for DCM. This article examines the extent to which existing research activity aligns with the established research priorities. Methods A systematic review of MEDLINE and Embase for “Cervical” AND “Myelopathy” was conducted following PRISMA guidelines. Full-text papers in English, exclusively studying DCM, published between January 1, 1995 and August 08, 2020 were considered eligible. Extracted data for each study included authors, journal, year of publication, location, sample size and study design. Each study was then analysed for alignment to the established research priorities. Results In total, 2261 papers with a total of 1,323,979 patients were included. Japan published more papers (625) than any other country. Moreover, 2005 (89%) of 2261 papers were aligned to at least one research priority. The alignment of papers to the different research priorities was unequal, with 1060 papers on the most researched priority alone (#15, predictors of outcome after treatment), but only 64 total papers on the least-researched 10 priorities. The comparative growth of research in the different priorities was also unequal, with some priorities growing and others plateauing over the past 5 years. Discussion Research activity in DCM continues to grow, and the focus of this research remains on surgery. The established research priorities therefore represent a new direction for the field.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Research activity amongst DCM research priorities

et al. 2021

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“…Within the field of DCM, there is inconsistent disease terminology, with an absence of index terms or codes [ 11 , 12 ], which makes literature searching extremely inefficient. For this reason, and to support work by Myelopathy.org, an international charity for DCM, building on original systematic reviews [ 13 , 14 ], a database of primary clinical trials exclusively related to DCM has been maintained [ 15 ].…”

Section: Methodsmentioning

confidence: 99%

Can co-authorship networks be used to predict author research impact? A machine-learning based analysis within the field of degenerative cervical myelopathy research

Grodzinski

Davies

2021

PLoS ONE

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Introduction Degenerative Cervical Myelopathy (DCM) is a common and disabling condition, with a relatively modest research capacity. In order to accelerate knowledge discovery, the AO Spine RECODE-DCM project has recently established the top priorities for DCM research. Uptake of these priorities within the research community will require their effective dissemination, which can be supported by identifying key opinion leaders (KOLs). In this paper, we aim to identify KOLs using artificial intelligence. We produce and explore a DCM co-authorship network, to characterise researchers’ impact within the research field. Methods Through a bibliometric analysis of 1674 scientific papers in the DCM field, a co-authorship network was created. For each author, statistics about their connections to the co-authorship network (and so the nature of their collaboration) were generated. Using these connectedness statistics, a neural network was used to predict H-Index for each author (as a proxy for research impact). The neural network was retrospectively validated on an unseen author set. Results DCM research is regionally clustered, with strong collaboration across some international borders (e.g., North America) but not others (e.g., Western Europe). In retrospective validation, the neural network achieves a correlation coefficient of 0.86 (p<0.0001) between the true and predicted H-Index of each author. Thus, author impact can be accurately predicted using only the nature of an author’s collaborations. Discussion Analysis of the neural network shows that the nature of collaboration strongly impacts an author’s research visibility, and therefore suitability as a KOL. This also suggests greater collaboration within the DCM field could help to improve both individual research visibility and global synergy.

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“…The result is that reliable study identification can only be done manually, with a consequent element of subjectivity. 6 Second, and perhaps more significant, outcome reporting in spinal surgery is extremely heterogeneous, with many different aspects of the disease measured, using different tools and at different time points. The result is that SRs often restrict their inclusion criteria to a specific tool.…”

Section: To the Editormentioning

confidence: 99%