Fundamentals of osteoarthritis. Rehabilitation: Exercise, diet, biomechanics, and physical therapist-delivered interventions

Dropout From Exercise Interventions in Adults With Knee or Hip Osteoarthritis: A Systematic Review and Meta-analysis

OBJECTIVE

To investigate the prevalence and moderators of dropout rates among adults with knee or hip osteoarthritis participating in exercise randomized controlled trials (RCTs).

DATA SOURCES

Two authors searched Embase, CINAHL, PsycARTICLES, and PubMed up to 01/09/2023.

STUDY SELECTION

We included RCTs of exercise interventions in people with knee or hip osteoarthritis that reported dropout rates.

DATA EXTRACTION

Dropout rates from exercise and control conditions and exerciser/participant, provider, and design/implementation related moderators.

DATA SYNTHESIS

In total, 209 RCTs involving 277 exercise arms in 13,102 participants were included (mean age at study level=64 years; median prevalence of men participants=26.8%). The trim-and-fill-adjusted prevalence of dropout across all RCTs was 17.5% (95% CI=16.7%-18.2%), which is comparable with dropout observed in control conditions (trim-and-fill-adjusted odds ratio=0.89; 95% CI=0.71-1.12, P=.37). Higher prevalence of antidepressant use at study-level predicted higher dropout (R2=0.75, P=.002, N RCTs=6, n exercisers=412). Supervision by an exercise professional was associated with lower dropout rates, with a trim-and-fill-adjusted rate of 13.2% (95% CI=11.7%-14.9%) compared with 20.8% without supervision (95% CI=18.3%-23.5%) (P<.001).

CONCLUSIONS

Dropout rates for exercise in RCTs are comparable with control conditions, suggesting that exercise is a generally well-accepted intervention. However, interventions should be supervised by an exercise professional, such as a physiotherapist or exercise physiologist, to further minimize the risk of dropout. Health professionals should consider participants' use of antidepressants as a risk factor for dropout from exercise.

Osteoarthritis year in review 2023: Biomechanics

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.