ABSTRACT
OBJECTIVE: The objective of the study was to evaluate the effectiveness of telehealth-based exercise intervention on pain, physical function and quality of life in patients with knee osteoarthritis. DESIGN: A systematic review and meta-analysis of randomised controlled trials (RCTs). METHODS: Six databases (PubMed, Embase, Cochrane Library, CINAHL, PEDro and Web of Science Core Collection) were searched for relevant randomised controlled trials published from database inception to 3 June 2021. Reviewers independently screened the literature, extracted data and used the Cochrane Collaboration Risk of Bias Tool for quality assessment. A meta-analysis and subgroup analyses, stratified by control condition, intervention duration and delivery type, were conducted by Revman 5.4. The study was reported in compliance with PRISMA statement. RESULTS: A total of 9 independent RCTs with 861 participants were included. The meta-analysis showed that the telehealth-based exercise interventions significantly reduced pain in KOA patients (SMD = -0.28, 95% CI [-0.49, -0.08], p < .01) and produced similar effects to controls in terms of physical function and quality of life. Subgroup analysis revealed that telehealth-based exercise interventions were superior to the use of exercise booklet and usual care in terms of pain and physical function and were similar to face-to-face exercise treatment; a long-term (>3 months) intervention and the use of web and smartphone APPs to deliver exercise interventions were associated with better pain relief and physical function. CONCLUSIONS: Telehealth-based exercise intervention is an effective strategy for KOA management during the COVID-19 epidemic, and it is significantly better than usual care in reducing knee pain and improving physical function and was able to achieve the effects of traditional face-to-face exercise treatment. Although the duration and type of delivery associated with the effect of the intervention have been identified, patient preference and acceptability need to be considered in practice.
ABSTRACT
It's urgently needed to assess the COVID-19 epidemic under the "dynamic zero-COVID policy" in China, which provides a scientific basis for evaluating the effectiveness of this strategy in COVID-19 control. Here, we developed a time-dependent susceptible-exposed-asymptomatic-infected-quarantined-removed (SEAIQR) model with stage-specific interventions based on recent Shanghai epidemic data, considering a large number of asymptomatic infectious, the changing parameters, and control procedures. The data collected from March 1st, 2022 to April 15th, 2022 were used to fit the model, and the data of subsequent 7 days and 14 days were used to evaluate the model performance of forecasting. We then calculated the effective regeneration number (R t) and analyzed the sensitivity of different measures scenarios. Asymptomatic infectious accounts for the vast majority of the outbreaks in Shanghai, and Pudong is the district with the most positive cases. The peak of newly confirmed cases and newly asymptomatic infectious predicted by the SEAIQR model would appear on April 13th, 2022, with 1963 and 28,502 cases, respectively, and zero community transmission may be achieved in early to mid-May. The prediction errors for newly confirmed cases were considered to be reasonable, and newly asymptomatic infectious were considered to be good between April 16th to 22nd and reasonable between April 16th to 29th. The final ranges of cumulative confirmed cases and cumulative asymptomatic infectious predicted in this round of the epidemic were 26,477 â¼ 47,749 and 402,254 â¼ 730,176, respectively. At the beginning of the outbreak, R t was 6.69. Since the implementation of comprehensive control, R t showed a gradual downward trend, dropping to below 1.0 on April 15th, 2022. With the early implementation of control measures and the improvement of quarantine rate, recovery rate, and immunity threshold, the peak number of infections will continue to decrease, whereas the earlier the control is implemented, the earlier the turning point of the epidemic will arrive. The proposed time-dependent SEAIQR dynamic model fits and forecasts the epidemic well, which can provide a reference for decision making of the "dynamic zero-COVID policy".