Multimodal data analysis of knee osteoarthritis assessment: factors selection for conservative care decision making. Issue 4 (12th March 2023)

• Record Type: Journal Article
• Authors: Bensalma, F.; Mezghani, N.; Cagnin, A.; Fuente, A.; Lenoir, L.; Hagemeister, N.
• Is Part Of: Computer methods in biomechanics and biomedical engineering. Volume 26:Issue 4(2023)
• Page Start: 450
• Page End: 459
• Publication Date: 2023-03-12
• Subjects: Assessment factors -- biomechanical -- clinical -- canonical correlation -- musculoskeletal -- multimodal CCA -- knee osteoarthritis (OA) -- radiographic grade; Biomechanics -- Data processing -- Periodicals; Biomedical engineering -- Periodicals; Biomechanics -- Periodicals; Biomedical Engineering -- methods -- Periodicals; Computing Methodologies -- Periodicals; 612.7
• DOI: 10.1080/10255842.2022.2066973
• Languages: English
• ISSNs: 1025-5842

Abstract

Abstract: When assessing a patient with knee osteoarthritis (OA), a number of factors are considered to guide treatment plan, namely, demographic, radiographic, clinical, musculoskeletal, and biomechanical factors. The aim of this study is to identify which of these factors are the most related to each other to potentially better prioritize the modifiable factors to be addressed as they may influence treatment outcomes. We investigated a multimodal canonical correlation analysis to evaluate associations between these factors. The analysis was performed on 415 OA patients who were not candidates for knee arthroplasty, to identify factors that are associated to the patients' clinical conditions.