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BackgroundSleep disturbance is common following hospitalisation both for COVID-19 and other causes. The clinical associations are poorly understood, despite it altering pathophysiology in other scenarios. We, therefore, investigated whether sleep disturbance is associated with dyspnoea along with relevant mediation pathways. MethodsSleep parameters were assessed in a prospective cohort of patients (n=2,468) hospitalised for COVID-19 in the United Kingdom in 39 centres using both subjective and device-based measures. Results were compared to a matched UK biobank cohort and associations were evaluated using multivariable linear regression. Findings64% (456/714) of participants reported poor sleep quality; 56% felt their sleep quality had deteriorated for at least 1-year following hospitalisation. Compared to the matched cohort, both sleep regularity (44.5 vs 59.2, p<0.001) and sleep efficiency (85.4% vs 88.5%, p<0.001) were lower whilst sleep period duration was longer (8.25h vs 7.32h, p<0.001). Overall sleep quality (effect estimate 4.2 (3.0-5.5)), deterioration in sleep quality following hospitalisation (effect estimate 3.2 (2.0-4.5)), and sleep regularity (effect estimate 5.9 (3.7-8.1)) were associated with both dyspnoea and impaired lung function (FEV1 and FVC). Depending on the sleep metric, anxiety mediated 13-42% of the effect of sleep disturbance on dyspnoea and muscle weakness mediated 29-43% of this effect. InterpretationSleep disturbance is associated with dyspnoea, anxiety and muscle weakness following COVID-19 hospitalisation. It could have similar effects for other causes of hospitalisation where sleep disturbance is prevalent. FundingUK Research and Innovation, National Institute for Health Research, and Engineering and Physical Sciences Research Council.
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ObjectivesTo describe physical behaviours following hospital admission for COVID-19 including associations with acute illness severity and ongoing symptoms. Methods1077 patients with COVID-19 discharged from hospital between March and November 2020 were recruited. Using a 14-day wear protocol, wrist-worn accelerometers were sent to participants after a five-month follow-up assessment. Acute illness severity was assessed by the WHO clinical progression scale, and the severity of ongoing symptoms was assessed using four previously reported data-driven clinical recovery clusters. Two existing control populations of office workers and type 2 diabetes were comparators. ResultsValid accelerometer data from 253 women and 462 men were included. Women engaged in a mean{+/-}SD of 14.9{+/-}14.7 minutes/day of moderate-to-vigorous physical activity (MVPA), with 725.6{+/-}104.9 minutes/day spent inactive and 7.22{+/-}1.08 hours/day asleep. The values for men were 21.0{+/-}22.3 and 755.5{+/-}102.8 minutes/day and 6.94{+/-}1.14 hours/day, respectively. Over 60% of women and men did not have any days containing a 30-minute bout of MVPA. Variability in sleep timing was approximately 2 hours in men and women. More severe acute illness was associated with lower total activity and MVPA in recovery. The very severe recovery cluster was associated with fewer days/week containing continuous bouts of MVPA, longer sleep duration, and higher variability in sleep timing. Patients post-hospitalisation with COVID-19 had lower levels of physical activity, greater sleep variability, and lower sleep efficiency than a similarly aged cohort of office workers or those with type 2 diabetes. ConclusionsPhysical activity and regulating sleep patterns are potential treatable traits for COVID-19 recovery programmes.
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BackgroundPre-existing comorbidities have been linked to SARS-CoV-2 infection but evidence is sparse on the importance and pattern of multimorbidity (2 or more conditions) and severity of infection indicated by hospitalisation or mortality. We aimed to use a multimorbidity index developed specifically for COVID-19 to investigate the association between multimorbidity and risk of severe SARS-CoV-2 infection. MethodsWe used data from the UK Biobank linked to laboratory confirmed test results for SARS-CoV-2 infection and mortality data from Public Health England between March 16 and July 26, 2020. By reviewing the current literature on COVID-19 we derived a multimorbidity index including: 1) angina; 2) asthma; 3) atrial fibrillation; 4) cancer; 5) chronic kidney disease; 6) chronic obstructive pulmonary disease; 7) diabetes mellitus; 8) heart failure; 9) hypertension; 10) myocardial infarction; 11) peripheral vascular disease; 12) stroke. Adjusted logistic regression models were used to assess the association between multimorbidity and risk of severe SARS-CoV-2 infection (hospitalisation or death). Potential effect modifiers of the association were assessed: age, sex, ethnicity, deprivation, smoking status, body mass index, air pollution, 25-hydroxyvitamin D, cardiorespiratory fitness, high sensitivity C-reactive protein. ResultsAmong 360,283 participants, the median age was 68 [range, 48-85] years, most were White (94.5%), and 1,706 had severe SARS-CoV-2 infection. The prevalence of multimorbidity was more than double in those with severe SARS-CoV-2 infection (25%) compared to those without (11%), and clusters of several multimorbidities were more common in those with severe SARS-CoV-2 infection. The most common clusters with severe SARS-CoV-2 infection were stroke with hypertension (79% of those with stroke had hypertension); diabetes and hypertension (72%); and chronic kidney disease and hypertension (68%). Multimorbidity was independently associated with a greater risk of severe SARS-CoV-2 infection (adjusted odds ratio 1.91 [95% confidence interval 1.70, 2.15] compared to no multimorbidity). The risk remained consistent across potential effect modifiers, except for greater risk among men. ConclusionThe risk of severe SARS-CoV-2 infection is higher in individuals with multimorbidity, indicating the need to target research and resources in people with SARS-CoV-2 infection and multimorbidity.
