Exercise reduces depressive symptoms in adults with arthritis: Evidential value

Interactive multiobjective optimization for finding the most preferred exercise therapy modality in knee osteoarthritis

BACKGROUND

There are no explicit guidelines or tools available to support clinicians in selecting exercise therapy modalities according to the characteristics of individual patients despite the apparent need.

OBJECTIVE

This study develops a methodology based on a novel multiobjective optimization model and examines its feasibility as a decision support tool to support healthcare professionals in comparing different modalities and identifying the most preferred one based on a patient's needs.

METHODS

Thirty-one exercise therapy modalities were considered from 21 randomized controlled trials. A novel interactive multiobjective optimization model was designed to characterize the efficacy of an exercise therapy modality based on five objectives: minimizing cost, maximizing pain reduction, maximizing disability improvement, minimizing the number of supervised sessions, and minimizing the length of the treatment period. An interactive model incorporates clinicians' preferences in finding the most preferred exercise therapy modality for each need. Multiobjective optimization methods are mathematical algorithms designed to identify the optimal balance between multiple conflicting objectives among available solutions/alternatives. They explicitly evaluate the conflicting objectives and support decision-makers in identifying the best balance. An experienced research-oriented physiotherapist was involved as a decision-maker in the interactive solution process testing the proposed decision support tool.

RESULTS

The proposed methodology design and interactive process of the tool, including preference information, graphs, and exercise suggestions following the preferences, can help clinicians to find the most preferred exercise therapy modality based on a patient's needs and health status; paving the way to individualize recommendations.

CONCLUSIONS

We examined the feasibility of our decision support tool using an interactive multiobjective optimization method designed to help clinicians balance between conflicting objectives to find the most preferred exercise therapy modality for patients with knee osteoarthritis. The proposed methodology is generic enough to be applied in any field of medical and healthcare settings, where several alternative treatment options exist.KEY MESSAGESWe demonstrate the potential of applying Interactive multiobjective optimization methods in a decision support tool to help clinicians compare different exercise therapy modalities and identify the most preferred one based on a patient's needs.The usability of the proposed decision support tool is tested and demonstrated in prescribing exercise therapy modalities to treat knee osteoarthritis patients.

Efficacy and Acceptability of Intermittent Aerobic Exercise on Polysomnography-Measured Sleep in People With Rheumatoid Arthritis With Self-Reported Sleep Disturbance: A Randomized Controlled Trial

OBJECTIVE

This study's objective was to investigate the efficacy and acceptability of intermittent aerobic exercise training on sleep parameters, fatigue, pain, depressive symptoms, physical function, and cardiorespiratory fitness in people with rheumatoid arthritis (RA).

METHODS

Thirty-eight people with RA were assigned to intermittent aerobic exercise training (three sessions/week for 6 weeks; intervention group, n = 17) or usual care (control group, n = 21). The primary outcome was a change in polysomnography-assessed sleep efficiency from baseline to the end of the intervention. Secondary outcomes were sleep quality (Pittsburgh Sleep Quality Index), fatigue (Bristol Rheumatoid Arthritis Fatigue Multi-Dimensional Questionnaire), depression (Center for Epidemiological Studies-Depression), and cardiorespiratory fitness (watt max test).

RESULTS

No between-group differences were found in changes in polysomnography-assessed sleep efficiency (0.04; 95% confidence interval [CI]: -0.02 to 0.09, P = 0.17). In the intervention group, sleep efficiency was improved significantly from baseline (0.84; 95% CI: 0.80-0.88) compared with the end of the intervention (6 weeks) (0.88; 95% CI: 0.85-0.92); however, there was no significant difference in the control group. Fatigue and depression measures were significantly lower in the intervention group than in the control group. Between-group differences were overall fatigue (-16.1; 95% CI: -25.1 to -7.0, P = 0.001), physical fatigue (-5.0; 95% CI: -7.3 to -2.7, P = 0.0001), cognitive fatigue (-2.4; 95% CI: -4.2 to 0.6, P = 0.009), living with fatigue (-2.5; 95% CI: -4.5 to -0.5, P = 0.01), and depressive symptoms (-6.8; 95% CI: -12.4 to -1.1, P = 0.02).

CONCLUSION

The intervention yielded no significantly better sleep efficiency compared with usual care. However, aspects of fatigue, including physical and cognitive fatigue, and depressive symptoms were significantly improved in the intervention group.

Determining factors related to poor quality of life in patients with axial spondyloarthritis: results from the British Society for Rheumatology Biologics Register (BSRBR-AS)

OBJECTIVE

To determine modifiable factors associated with poor quality of life (QoL) in patients with axial spondyloarthritis (axSpA).

METHODS

Analysis of data from the British Society for Rheumatology Biologics Register in Ankylosing Spondylitis (BSRBR-AS) and validation of a previous model using data from 1810 patients with axSpA recruited during 2012-2017. Data collected included clinical and patient-reported measures. QoL was assessed using the Ankylosing Spondylitis Quality of Life (ASQoL) measure. Linear regression models predicting ASQoL scores were used first to validate a previous model from a national study, to extend this with additional information available in BSRBR-AS and finally to identify a 'de novo' model from BSRBR-AS of which factors impact on poor QoL.

RESULTS

Four out of five factors included in a previous model of poor QoL in patients with axSpA were confirmed: Bath Ankylosing Spondylitis Disease Activity Index and Bath Ankylosing Spondylitis Functional Index, fatigue and widespread pain, although the performance of the model was improved by the addition of measures of mood and sleep disturbance. In a de novo model in BSRBR-AS, there were six factors (other than disease activity and function) that predicted ASQoL: depression (β=0.16), sleep disturbance (β=0.08), activity impairment (β=0.04), fibromyalgia (Symptom Severity Scale (β=0.24) and Widespread Pain Index (β=0.10)) and tobacco smoking (β=0.66).

CONCLUSION

This study confirms that poor QoL in patients with axSpA, in addition to high disease activity and poor function, is independently influenced by sleep disturbance, mood and widespread pain. These additional factors are not considered targets for treatment in current European League Against Rheumatism (EULAR) guidelines for managing the condition.