The Influence of Tai Chi Exercise on Proprioception in Patients with Knee Osteoarthritis: Results from a Pilot Randomized Controlled Trial

Effects of mind-body exercise on knee osteoarthritis: a systematic review and meta-analysis of randomized controlled trials

OBJECTIVE

To evaluate the effect of mind-body exercise on improving knee osteoarthritis (KOA) and thereby informing osteoarthritis exercise rehabilitation.

METHODS

The China National Knowledge Infrastructure (CNKI), Wanfang, PubMed/Medline, Cochrane Library, Web of Science, EBSCO, Embase, Scopus, and ProQuest databases were searched to identify randomized controlled trials (RCTs) that involved tai chi, yoga, and baduanjin interventions for KOA. The search period ranged from inception to October 25, 2022. The methodological quality of the included studies was evaluated by the Cochrane risk of bias assessment tool, and the included data were statistically analyzed and plotted using Review Manager 5.3 and Stata 14.0 software.

RESULTS

We included 17 articles with a total of 1122 patients. Compared with the control group, mind-body exercise significantly improved patient pain (standardized mean difference (SMD) = -0.65, 95% confidence interval (CI) [-0.87, -0.42], p < 0.00001), stiffness (SMD = -0.75, 95% CI [-1.05, -0.45], p < 0.00001), physical function (SMD = -0.82, 95% CI [-1.03, -0.62], p < 0.00001), mental health (SMD = 0.31, 95% CI [0.11, 0.51], p = 0.002), and depression (SMD = -0.32, 95% CI [-0.50, -0.15], p = 0.0003). In terms of motor ability, mind-body exercise significantly increased the 6-min walking distance (SMD = 18.45, 95% CI [5.80, 31.10], p = 0.004) and decreased timed up and go test time (SMD = -1.15, 95% CI [-1.71, -0.59], p < 0.0001).

CONCLUSIONS

The current study showed that mind-body exercise is safe and effective for KOA patients. However, given the methodological limitations of the included studies, additional high-quality evidence is needed to support the conclusions of this study.

Prediction of knee joint pain in Tai Chi practitioners: a cross-sectional machine learning approach

OBJECTIVE

To build a supervised machine learning-based classifier, which can accurately predict whether Tai Chi practitioners may experience knee pain after years of exercise.

DESIGN

A prospective approach was used. Data were collected using face-to-face through a self-designed questionnaire.

SETTING

Single centre in Shanghai, China.

PARTICIPANTS

A total of 1750 Tai Chi practitioners with a course of Tai Chi exercise over 5 years were randomly selected.

MEASURES

All participants were measured by a questionnaire survey including personal information, Tai Chi exercise pattern and Irrgang Knee Outcome Survey Activities of Daily Living Scale. The validity of the questionnaire was analysed by logical analysis and test, and the reliability of this questionnaire was mainly tested by a re-test method. Dataset 1 was established by whether the participant had knee pain, and dataset 2 by whether the participant's knee pain affected daily living function. Then both datasets were randomly assigned to a training and validating dataset and a test dataset in a ratio of 7:3. Six machine learning algorithms were selected and trained by our dataset. The area under the receiver operating characteristic curve was used to evaluate the performance of the trained models, which determined the best prediction model.

RESULTS

A total of 1703 practitioners completed the questionnaire and 47 were eliminated for lack of information. The total reliability of the scale is 0.94 and the KMO (Kaiser-Meyer-Olkin measure of sampling adequacy) value of the scale validity was 0.949 (>0.7). The CatBoost algorithm-based machine-learning model achieved the best predictive performance in distinguishing practitioners with different degrees of knee pain after Tai Chi practice. 'Having knee pain before Tai Chi practice', 'knee joint warm-up' and 'duration of each exercise' are the top three factors associated with pain after Tai Chi exercise in the model. 'Having knee pain before Tai Chi practice', 'Having Instructor' and 'Duration of each exercise' were most relevant to whether pain interfered with daily life in the model.

CONCLUSION

CatBoost-based machine learning classifier accurately predicts knee pain symptoms after practicing Tai Chi. This study provides an essential reference for practicing Tai Chi scientifically to avoid knee pain.

The effects of exercise training on knee repositioning sense in people with knee osteoarthritis: a systematic review and meta-analysis of clinical trials

OBJECTIVE

Osteoarthritis (OA) of the knee is one of the most common global joint disorders, especially in aging population, and is among leading health-related concerns of societies. Therefore, this systematic review and meta-analysis was done to investigate the results related to the effects of exercise interventions on knee repositioning sense in patients with knee OA.

METHODS

An extensive search was independently performed in electronic databases including PubMed, MEDLINE, Web of Science, SCOPUS, and Google Scholar, to identify randomized clinical trials (RCTs) conducted on knee OA and to evaluate knee repositioning sense before and after different exercise interventions. After extracting relevant data from eligible studies, results of the studies were pooled using a random-effects model of meta-analysis. The Physiotherapy Evidence Database (PEDro) of clinical trials was used for quality assessment of eligible studies.

RESULTS

Among 2702 studies identified in the initial search, 17 studies were eligible for final systematic review and meta-analysis. The results showed that the patients who participated in different exercise interventions had significantly less knee repositioning error (mean differences: -1.141 degrees (95%CI: -1.510, -0.772, P < .001) compared to those who did not undergo exercise interventions. The eligible studies exhibited publication bias (Intercept: -6.69, P = .002), and the data showed significant heterogeneity (I2 = 85.633%, Q = 153.125, P < .001). Moreover, meta regression showed more prolonged exercise duration might have more effects on knee repositioning error (Coefficient=-0.860, 95% CI=-1.705, -0.016, Z=-2.00, P = .045).

CONCLUSION

There is strong evidence that exercise interventions may effectively reduce knee repositioning error. Moreover, it seems that more prolonged exercise duration may be associated with the greater effect size.

The Effects of Baduanjin Qigong on Postural Stability, Proprioception, and Symptoms of Patients With Knee Osteoarthritis: A Randomized Controlled Trial

Background: Knee osteoarthritis is a common disease affecting a large number of old individuals worldwide. This study aimed to explore the effects of Baduanjin Qigong in patients with knee osteoarthritis. Methods: Fifty participants with knee osteoarthritis were randomly assigned to either an experimental group (n = 25) or a control group (n = 25). Participants in the experimental group received Baduanjin Qigong training for 12 weeks, with three sessions per week lasting 40 min per session. Participants in the control group did not receive any additional physical training. All of participants completed outcome (proprioception, postural stability, and functional ability) assessments at three time points (baseline, Week 8, 12). Results: Proprioception and Western Ontario and McMaster Universities Osteoarthritis Index function were statistically improved at eighth and 12th week of the intervention in the Baduanjin Qigong group (p < 0.05), while the control group did not have any significant changes. For postural stability at the anterior-posterior direction with eyes closed, Baduanjin Qigong group showed significant improvement compared to controls after the 12 weeks of intervention (p < 0.05). Conclusions: Regular Baduanjin Qigong practice helped the improvement of knee joint proprioception and postural stability, and reduction of pain, stiffness, and functional impairments of old adults with knee osteoarthritis. Well-designed randomized controlled trials with long-term assessment are needed. The trial was registered in Chinese Clinical Trial Registry (ChiCTR-IOR-16010042). URL: http://www.chictr.org.cn/hvshowproject.aspx?id=10550.