Osteoarthritis year in review 2023: Biomechanics.

Autor: Diamond LE; Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Gold Coast, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast, Australia. Electronic address: l.diamond@griffith.edu.au., Grant T; Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Gold Coast, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast, Australia. Electronic address: tamara.grant@griffithuni.edu.au., Uhlrich SD; Department of Bioengineering, Stanford University, Stanford, CA, USA. Electronic address: suhlrich@stanford.edu.
Jazyk: angličtina
Zdroj: Osteoarthritis and cartilage [Osteoarthritis Cartilage] 2024 Feb; Vol. 32 (2), pp. 138-147. Date of Electronic Publication: 2023 Dec 02.
DOI: 10.1016/j.joca.2023.11.015
Abstrakt: Biomechanics plays a significant yet complex role in osteoarthritis (OA) onset and progression. Identifying alterations in biomechanical factors and their complex interactions is critical for gaining new insights into OA pathophysiology and identification of clearly defined and modifiable mechanical treatment targets. This review synthesized biomechanics studies from March 2022 to April 2023, from which three themes relating to human gait emerged: (1) new insights into the pathogenesis of OA using computational modeling and machine learning, (2) technology-enhanced biomechanical interventions for OA, and (3) out-of-lab biomechanical assessments of OA. We further highlighted future-focused areas which may continue to advance the field of biomechanics in OA, with a particular emphasis on exploiting technology to understand and treat biomechanical mechanisms of OA outside the laboratory. The breadth of studies included in this review highlights the complex role of biomechanics in OA and showcase numerous innovative and outstanding contributions to the field. Exciting cross-disciplinary efforts integrating computational modeling, mobile sensors, and machine learning methods show great promise for streamlining in vivo multi-scale biomechanics workflows and are expected to underpin future breakthroughs in the understanding and treatment of biomechanics in OA.
(Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)
Databáze: MEDLINE
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