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The use of technology in the subcategorisation of osteoarthritis : a Delphi study approach
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Mennan, Claire, Hopkins, Timothy, Channon, Alastair, Elliott, Mark T., Johnstone, Brian, Kadir, Timor, Loughlin, John, Peffers, Mandy, Pitsillides, Andrew, Sofat, Nidhi, Stewart, Caroline, Watt, Fiona E., Zeggini, Eleftheria, Holt, Cathy and Roberts, Sally (2020) The use of technology in the subcategorisation of osteoarthritis : a Delphi study approach. Osteoarthritis and Cartilage Open, 2 (3). 100081. doi:10.1016/j.ocarto.2020.100081
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WRAP-use-technology-subcategorisation-osteoarthritis-Delphi-study-approach-Elliot-2020.pdf - Accepted Version - Requires a PDF viewer. Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0. Download (862Kb) | Preview |
Official URL: http://dx.doi.org/10.1016/j.ocarto.2020.100081
Abstract
Objective:
This UK-wide OATech+ Network consensus study utilised a Delphi approach to discern levels. of awareness across an expert panel regarding the role of existing and novel technologies in osteoarthritis research. To direct future cross-disciplinary research it aimed to identify which could be adopted to subcategorise patients with osteoarthritis (OA).
Design:
An online questionnaire was formulated based on technologies which might aid OA research and subcategorisation. During a two-day face-to-face meeting concordance of expert opinion was established with surveys (23 questions) before, during and at the end of the meeting (Rounds 1,2 and 3, respectively). Experts spoke on current evidence for imaging, genomics, epigenomics, proteomics, metabolomics, biomarkers, activity monitoring, clinical engineering and machine learning relating to subcategorisation. For each round of voting, ≥80% votes led to consensus and ≤20% to exclusion of a statement.
Results:
Panel members were unanimous that a combination of novel technological advances have potential to improve OA diagnostics and treatment through subcategorisation,. agreeing in Rounds 1 and 2 that epigenetics, genetics, MRI, proteomics, wet biomarkers and machine learning could aid subcategorisation. Expert presentations changed participants’ opinions on the value of metabolomics, activity monitoring and clinical engineering, all reaching consensus in Round 2. X-rays lost consensus between Rounds 1 and 2; clinical X-rays reached consensus in Round 3.
Conclusion:
Consensus identified that 9 of the 11 technologies should be targeted towards OA subcategorisation to address existing OA research technology and knowledge gaps. These novel, rapidly evolving technologies are recommended as a focus for emergent, cross-disciplinary osteoarthritis research programmes.
| Item Type: | Journal Article | |||||||||||||||||||||||||||||||||||||||
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| Subjects: | R Medicine > RA Public aspects of medicine R Medicine > RC Internal medicine |
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| Divisions: | Faculty of Science > WMG (Formerly the Warwick Manufacturing Group) | |||||||||||||||||||||||||||||||||||||||
| Library of Congress Subject Headings (LCSH): | Osteoarthritis | |||||||||||||||||||||||||||||||||||||||
| Journal or Publication Title: | Osteoarthritis and Cartilage Open | |||||||||||||||||||||||||||||||||||||||
| Publisher: | Elsevier Ltd | |||||||||||||||||||||||||||||||||||||||
| ISSN: | 26659131 | |||||||||||||||||||||||||||||||||||||||
| Official Date: | September 2020 | |||||||||||||||||||||||||||||||||||||||
| Dates: |
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| Volume: | 2 | |||||||||||||||||||||||||||||||||||||||
| Number: | 3 | |||||||||||||||||||||||||||||||||||||||
| Article Number: | 100081 | |||||||||||||||||||||||||||||||||||||||
| DOI: | 10.1016/j.ocarto.2020.100081 | |||||||||||||||||||||||||||||||||||||||
| Status: | Peer Reviewed | |||||||||||||||||||||||||||||||||||||||
| Publication Status: | Published | |||||||||||||||||||||||||||||||||||||||
| Access rights to Published version: | Open Access | |||||||||||||||||||||||||||||||||||||||
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