ABSTRACT
Objective: To examine changes in physical activity, sleep, pain and mood in people with knee osteoarthritis (OA) during the ongoing COVID-19 pandemic by leveraging an ongoing randomized clinical trial (RCT). Methods: Participants enrolled in a 12-month parallel two-arm RCT (NCT03064139) interrupted by the COVID-19 pandemic wore an activity monitor (Fitbit Charge 3) and filled out custom weekly surveys rating knee pain, mood, and sleep as part of the study. Data from 30 weeks of the parent study were used for this analysis. Daily step count and sleep duration were extracted from activity monitor data, and participants self-reported knee pain, positive mood, and negative mood via surveys. Metrics were averaged within each participant and then across all participants for pre-pandemic, stay-at-home, and reopening periods, reflecting the phased re-opening in the state of Massachusetts. Results: Data from 28 participants showed small changes with inconclusive clinical significance during the stay-at-home and reopening periods compared to pre-pandemic for all outcomes. Summary statistics suggested substantial variability across participants with some participants showing persistent declines in physical activity during the observation period. Conclusion: Effects of the COVID-19 pandemic on physical activity, sleep, pain, and mood were variable across individuals with OA. Specific reasons for this variability could not be determined. Identifying factors that could affect individuals with knee OA who may exhibit reduced physical activity and/or worse symptoms during major lifestyle changes (such as the ongoing pandemic) is important for providing targeted healthcare services and management advice towards those that could benefit from it the most.
ABSTRACT
BACKGROUND: The effectiveness of interleukin-6 inhibitors (IL-6i) in ameliorating coronavirus disease 2019 (COVID-19) remains uncertain. METHODS: We analyzed data for patients aged ≥18 years admitted with a positive severe acute respiratory syndrome coronavirus 2 polymerase chain reaction test at 4 safety-net hospital systems with diverse populations and high rates of medical comorbidities in 3 US regions. We used inverse probability of treatment weighting via machine learning for confounding adjustment by demographics, comorbidities, and disease severity markers. We estimated the average treatment effect, the odds of IL-6i effect on in-hospital mortality from COVID-19, using a logistic marginal structural model. RESULTS: Of 516 patients, 104 (20.1%) received IL-6i. Estimate of the average treatment effect adjusted for confounders suggested a 37% reduction in odds of in-hospital mortality in those who received IL-6i compared with those who did not, although the confidence interval included the null value of 1 (odds ratioâ =â 0.63; 95% confidence interval, .29-1.38). A sensitivity analysis suggested that potential unmeasured confounding would require a minimum odds ratio of 2.55 to nullify our estimated IL-6i effect size. CONCLUSIONS: Despite low precision, our findings suggested a relatively large effect size of IL-6i in reducing the odds of COVID-19-related in-hospital mortality.