Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study

Introduction: The multiorgan impact of moderate to severe coronavirus infections in the post-acute phase is still poorly understood. We aimed to evaluate the excess burden of multiorgan abnormalities after hospitalisation with COVID-19, evaluate their determinants, and explore associations with patient-related outcome measures. Methods: In a prospective, UK-wide, multicentre MRI follow-up study (C-MORE), adults (aged ≥18 years) discharged from hospital following COVID-19 who were included in Tier 2 of the Post-hospitalisation COVID-19 study (PHOSP-COVID) and contemporary controls with no evidence of previous COVID-19 (SARS-CoV-2 nucleocapsid antibody negative) underwent multiorgan MRI (lungs, heart, brain, liver, and kidneys) with quantitative and qualitative assessment of images and clinical adjudication when relevant. Individuals with end-stage renal failure or contraindications to MRI were excluded. Participants also underwent detailed recording of symptoms, and physiological and biochemical tests. The primary outcome was the excess burden of multiorgan abnormalities (two or more organs) relative to controls, with further adjustments for potential confounders. The C-MORE study is ongoing and is registered with ClinicalTrials.gov, NCT04510025. Findings: Of 2710 participants in Tier 2 of PHOSP-COVID, 531 were recruited across 13 UK-wide C-MORE sites. After exclusions, 259 C-MORE patients (mean age 57 years [SD 12]; 158 [61%] male and 101 [39%] female) who were discharged from hospital with PCR-confirmed or clinically diagnosed COVID-19 between March 1, 2020, and Nov 1, 2021, and 52 non-COVID-19 controls from the community (mean age 49 years [SD 14]; 30 [58%] male and 22 [42%] female) were included in the analysis. Patients were assessed at a median of 5·0 months (IQR 4·2–6·3) after hospital discharge. Compared with non-COVID-19 controls, patients were older, living with more obesity, and had more comorbidities. Multiorgan abnormalities on MRI were more frequent in patients than in controls (157 [61%] of 259 vs 14 [27%] of 52; p<0·0001) and independently associated with COVID-19 status (odds ratio [OR] 2·9 [95% CI 1·5–5·8]; padjusted=0·0023) after adjusting for relevant confounders. Compared with controls, patients were more likely to have MRI evidence of lung abnormalities (p=0·0001; parenchymal abnormalities), brain abnormalities (p<0·0001; more white matter hyperintensities and regional brain volume reduction), and kidney abnormalities (p=0·014; lower medullary T1 and loss of corticomedullary differentiation), whereas cardiac and liver MRI abnormalities were similar between patients and controls. Patients with multiorgan abnormalities were older (difference in mean age 7 years [95% CI 4–10]; mean age of 59·8 years [SD 11·7] with multiorgan abnormalities vs mean age of 52·8 years [11·9] without multiorgan abnormalities; p<0·0001), more likely to have three or more comorbidities (OR 2·47 [1·32–4·82]; padjusted=0·0059), and more likely to have a more severe acute infection (acute CRP >5mg/L, OR 3·55 [1·23–11·88]; padjusted=0·025) than those without multiorgan abnormalities. Presence of lung MRI abnormalities was associated with a two-fold higher risk of chest tightness, and multiorgan MRI abnormalities were associated with severe and very severe persistent physical and mental health impairment (PHOSP-COVID symptom clusters) after hospitalisation. Interpretation: After hospitalisation for COVID-19, people are at risk of multiorgan abnormalities in the medium term. Our findings emphasise the need for proactive multidisciplinary care pathways, with the potential for imaging to guide surveillance frequency and therapeutic stratification

Development of a database for chemical mechanism assignments for volatile organic emissions

<div><p>The development of a database for making model species assignments when preparing total organic gas (TOG) emissions input for atmospheric models is described. This database currently has assignments of model species for 12 different gas-phase chemical mechanisms for over 1700 chemical compounds and covers over 3000 chemical categories used in five different anthropogenic TOG profile databases or output by two different biogenic emissions models. This involved developing a unified chemical classification system, assigning compounds to mixtures, assigning model species for the mechanisms to the compounds, and making assignments for unknown, unassigned, and nonvolatile mass. The comprehensiveness of the assignments, the contributions of various types of speciation categories to current profile and total emissions data, inconsistencies with existing undocumented model species assignments, and remaining speciation issues and areas of needed work are also discussed. The use of the system to prepare input for SMOKE, the Speciation Tool, and for biogenic models is described in the supplementary materials. The database, associated programs and files, and a users manual are available online at <a href="http://www.cert.ucr.edu/~carter/emitdb." target="_blank">http://www.cert.ucr.edu/~carter/emitdb</a>.</p><p>Implications: <i>Assigning air quality model species to the hundreds of emitted chemicals is a necessary link between emissions data and modeling effects of emissions on air quality. This is not easy and makes it difficult to implement new and more chemically detailed mechanisms in models. If done incorrectly, it is similar to errors in emissions speciation or the chemical mechanism used. Nevertheless, making such assignments is often an afterthought in chemical mechanism development and emissions processing, and existing assignments are usually undocumented and have errors and inconsistencies. This work is designed to address some of these problems.</i></p></div

Prevalence of physical frailty, including risk factors, up to 1 year after hospitalisation for COVID-19 in the UK: a multicentre, longitudinal cohort studyResearch in context

Summary: Background: The scale of COVID-19 and its well documented long-term sequelae support a need to understand long-term outcomes including frailty. Methods: This prospective cohort study recruited adults who had survived hospitalisation with clinically diagnosed COVID-19 across 35 sites in the UK (PHOSP-COVID). The burden of frailty was objectively measured using Fried's Frailty Phenotype (FFP). The primary outcome was the prevalence of each FFP group—robust (no FFP criteria), pre-frail (one or two FFP criteria) and frail (three or more FFP criteria)—at 5 months and 1 year after discharge from hospital. For inclusion in the primary analysis, participants required complete outcome data for three of the five FFP criteria. Longitudinal changes across frailty domains are reported at 5 months and 1 year post-hospitalisation, along with risk factors for frailty status. Patient-perceived recovery and health-related quality of life (HRQoL) were retrospectively rated for pre-COVID-19 and prospectively rated at the 5 month and 1 year visits. This study is registered with ISRCTN, number ISRCTN10980107. Findings: Between March 5, 2020, and March 31, 2021, 2419 participants were enrolled with FFP data. Mean age was 57.9 (SD 12.6) years, 933 (38.6%) were female, and 429 (17.7%) had received invasive mechanical ventilation. 1785 had measures at both timepoints, of which 240 (13.4%), 1138 (63.8%) and 407 (22.8%) were frail, pre-frail and robust, respectively, at 5 months compared with 123 (6.9%), 1046 (58.6%) and 616 (34.5%) at 1 year. Factors associated with pre-frailty or frailty were invasive mechanical ventilation, older age, female sex, and greater social deprivation. Frail participants had a larger reduction in HRQoL compared with before their COVID-19 illness and were less likely to describe themselves as recovered. Interpretation: Physical frailty and pre-frailty are common following hospitalisation with COVID-19. Improvement in frailty was seen between 5 and 12 months although two-thirds of the population remained pre-frail or frail. This suggests comprehensive assessment and interventions targeting pre-frailty and frailty beyond the initial illness are required. Funding: UK Research and Innovation and National Institute for Health Research